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Crop multi-model ensembles (MME) have proven to be effective in increasing the accuracy of simulations in modelling experiments. However, the ability of MME to capture crop responses to changes in sowing dates and densities has not yet been investigated. These management interventions are some of the main levers for adapting cropping systems to climate change. Here, we explore the performance of a MME of 29 wheat crop models to predict the effect of changing sowing dates and rates on yield and yield components, on two sites located in a high-yielding environment in New Zealand. The experiment was conducted for 6 years and provided 50 combinations of sowing date, sowing density and growing season. We show that the MME simulates seasonal growth of wheat well under standard sowing conditions, but fails under early sowing and high sowing rates. The comparison between observed and simulated in-season fraction of intercepted photosynthetically active radiation (FIPAR) for early sown wheat shows that the MME does not capture the decrease of crop above ground biomass during winter months due to senescence. Models need to better account for tiller competition for light, nutrients, and water during vegetative growth, and early tiller senescence and tiller mortality, which are exacerbated by early sowing, high sowing densities, and warmer winter temperatures. [ABSTRACT FROM AUTHOR]

• N 2 O emission module was coupled to three agroecosystem models. • Uncertainty in the key variables of the N 2 O module was characterized. • NO 3 − and NH 4 + peaks show great variabiliy between models. • These peaks depend on the representation of soil processes in the models. • Wet acidic soils are more challenging for agroecosystem models to simulate. Nitrogen fertilization is a key agronomic lever for high crop productivity, but also an important source of N 2 O emission, a potent greenhouse gas. Process-based agroecosystem simulation models are popular tools for managing the timing and amount of fertilization, and help reduce N 2 O emissions. However, accurate simulation of N 2 O emissions at field scale is still a challenge due to the spatial and temporal variability of the soil conditions. In this study, we investigated the sources of structural uncertainty in predicting N 2 O emissions under a wide range of pedo-climatic conditions using a representative field data set. We implemented the same nitrification/denitrification/N 2 O emission formalism in three different agroecosystem models and analyzed how the inter-model variability of variables involved in nitrification and denitrification processes, affected the simulated N 2 O emissions. We characterized the dispersion of the key variables (water-filled pore space, NO 3 − and NH 4 + concentration, and soil temperature) between models and we evaluated the effect of variable uncertainty on N 2 O emissions uncertainty using a sensitivity analysis. We also analyzed model errors over a wide range of soil-climate conditions to identify the most challenging conditions for simulation, which require further model improvement. Our results highlighted that the simulation of the timing and amplitude of the NO 3 − and NH 4 + peaks was highly variable between agroecosystem models, with an important impact on N 2 O emission. These peaks occurred mainly after fertilization or incorporation of crop residues, and the different representations of fertilization and mineralization between the models had a major effect on the simulation of N 2 O emissions. Our analysis also emphasized that wet acidic soils with high denitrification potential are more challenging for models to simulate. [ABSTRACT FROM AUTHOR]

Climate-induced changes in the physical, chemical, and biological environment are expected to increasingly stress marine ecosystems, with important consequences for fisheries exploitation. Here, we use the APECOSM-E numerical model (Apex Predator ECOSystem Model - Estimation) to evaluate the future impacts of climate change on the physiology, spatial distribution, and abundance of skipjack tuna, the worldwide most fished species of tropical tuna. The main novelties of our approach lie in the mechanistic link between environmental factors, metabolic rates, and behavioral responses and in the fully three dimensional representation of habitat and population abundance. Physical and biogeochemical fields used to force the model are provided by the last generation of the IPSL- CM5 Earth System Model run from 1990 to 2100 under a 'business-as-usual' scenario ( RCP8.5). Our simulations show significant changes in the spatial distribution of skipjack tuna suitable habitat, as well as in their population abundance. The model projects deterioration of skipjack habitat in most tropical waters and an improvement of habitat at higher latitudes. The primary driver of habitat changes is ocean warming, followed by food density changes. Our projections show an increase of global skipjack biomass between 2010 and 2050 followed by a marked decrease between 2050 and 2095. Spawning rates are consistent with population trends, showing that spawning depends primarily on the adult biomass. On the other hand, growth rates display very smooth temporal changes, suggesting that the ability of skipjack to keep high metabolic rates in the changing environment is generally effective. Uncertainties related to our model spatial resolution, to the lack or simplification of key processes and to the climate forcings are discussed. [ABSTRACT FROM AUTHOR]

The benefits of implementing no-take Marine Protected Areas (MPAs) for the conservation of highly migratory species are not easy to assess. They depend on several factors, such as the fish mobility, fisher behaviour and the area covered by the MPA with respect to the distribution area of the species to protect. In this study, we explore the simultaneous effects of MPAs and fishing scenarios on skipjack tuna population dynamics, using the spatially-explicit APECOSM-E model. The model represents the size-structured population dynamics of skipjack tuna in the Indian Ocean and their dependence on climatic variability and exploitation by fisheries. Numerical experiments were run from the beginning of industrial fisheries in the early 1980s to the year 2030, considering different scenarios for the future development of fisheries. These scenarios combined different trends in fishing effort and technological development, either assuming a continuous increase following historical trends or a stabilization of these factors at present values. The simulations were designed to explore the effects of two MPAs of different size and location: the recently established Chagos MPA, and a hypothetical MPA covering a large part of the Western Indian Ocean, where most of the skipjack catches are presently made. We modelled the redistribution of fishing effort around the MPAs assuming that the fishers had partial knowledge of the spatial distribution of the skipjack population. The effects of the two MPAs on the population dynamics, catch and fishing mortality are shown. Our results revealed a very minor effect of the Chagos MPA on the skipjack tuna population, while the Western Indian Ocean MPA had an important impact on the fishing mortality and succeeded in stabilizing the spawning population. The simulations also showed that the effect of an MPA depends on the evolution of fisheries and it is therefore important to explore different fishery scenarios to assess the future benefits of an MPA. [ABSTRACT FROM AUTHOR]

Abstract: This paper presents the parameter estimation and sensitivity analysis of the APECOSM-E model, which describes the basin scale 3D size-structured population dynamics of the skipjack tuna population in the Indian Ocean under the joint effect of environmental variability and fisheries exploitation. The model is presented in detail in the companion paper (Dueri et al., 2012). A common methodology based on the evaluation of a cost function that combines the negative log-likelihoods of commercial catches and size frequencies is used for both tasks. A Bayesian term representing the a priori probabilities about the model parameters is added to the cost function used for parameter estimation. The partial derivatives of the cost function with respect to the parameters are obtained by deriving the tangent linear code of the model by automatic differentiation of the direct code. A minimization algorithm is used to estimate the parameters related to fisheries and maximise the fitness of the model to the available observations. In a second step, we evaluate the local sensitivity of the non-estimated parameters and identify the model parameters that have an important effect on the output of the model and that would deserve better measurements in order to reduce the level of uncertainty in the model outputs. The comparison between the optimized simulation and the observations allows identifying the model''s strengths and limitations, in the perspective of using the model to test scenarios concerning the resilience of the population and the sustainability of its exploitation in the Indian Ocean. [Copyright &y& Elsevier]

Abstract: APECOSM-E (Apex-Predator-Ecosystem-Model-Estimation) is a deterministic model that represents the 3D distribution and population dynamics of tropical tuna under the joint effect of environmental conditions and exploitation by fisheries. It is a simplified version of the top predator component of the APECOSM framework, based on a single partial differential equation. The model is structured in 3D space and fish size and considers size dependent reproduction, growth, predation, natural mortality and fishing mortality. Processes are time, space and size-dependent and linked to the environment through mechanistic bioenergetic or behavioral parameterizations. Physiological rates such as growth, reproduction and ageing mortality are derived from the Dynamic Energy Budget (DEB) theory, while horizontal movements and vertical distribution obey a mechanistically derived advection–diffusion formulation driven by habitat gradients and oceanic currents. The effect of fishing is accounted for through the use of fleet-specific size and depth selectivity functions and time-dependent catchability coefficients which relate observed fishing effort to catches and size-frequencies. In this paper we present the mathematical formulations of the physiological and behavioral components of the model, and an application to the skipjack tuna population in the Indian Ocean. The model is run with a daily time step on a 1°×1° horizontal grid and considers 20 vertical layers, reaching a maximal depth of 500m. Results show the effects of spatial and temporal variability of environmental conditions on tuna physiology in terms of growth, reproduction and survival. Moreover, our results suggest that observed trends in reported catches are connected to environmental conditions by means of recruitment dynamics. In addition, the model allows representing the horizontal and vertical distribution of skipjack tuna and assessing the effect of accessibility of the resource to fisheries. The ability of the model to represent the distribution of biomass in accordance with the pattern given by the observed fishing activity was evaluated by comparing the spatial distribution of the simulated biomass with the observed distribution of commercial purse seiners and bait boats catches in the Indian Ocean. The likelihood based method used for estimating the model parameters as well as an analysis of its sensitivity to their values is provided in a companion paper (Dueri et al., 2012). [Copyright &y& Elsevier]

A 1D coupled hydrodynamic and contaminant fate model was applied to simulate the distribution of polychlorinated biphenyls (PCBs) in the Ispra Bay located in the southern part of Lake Maggiore (Italy). The model succeeded in representing the hydrodynamic processes occurring in the lake such as thermal stratification during summer 2005 followed by the complete mixing of the water column in February 2006. The results of the PCB fate model highlighted that these processes play a key role for the settling of particles and consequently for the distribution of PCBs in the water column as well as for the contaminant flux at the sediment–water interface. On the air–water front, the simulations emphasised that the net atmospheric PCB input fluxes are generally more important during the cold season and show peaks during periods of high wet deposition. Finally, the seasonal variability of the distribution of PCB in the water column was assessed. [Copyright &y& Elsevier]

A review of experimental data has been performed to study the relationships between the concentration in water, pore water and sediments for different families of organic contaminants. The objective was to determine whether it is possible to set EQS for sediments from EQS defined for surface waters in the Daughter Directive of the European Parliament (COM (2006) 397). The analysis of experimental data showed that even though in some specific cases there is a coupling between water column and sediments, this coupling is rather the exception. Therefore it is not recommendable to use water column data to assess the chemical quality status of sediments and it is necessary to measure in both media. At the moment EQS have been defined for the water column and will assess only the compliance with good chemical status of surface waters. Since the sediment toxicity depends on the dissolved pore water concentration, the EQS developed for water could be applied to pore water (interstitial water); hence, there would be no need of developing another set of EQS. The partitioning approach has been proposed as a solution to calculate sediment EQS from water EQS, but the partitioning coefficient strongly depends on sediment characteristics and its use introduces an important uncertainty in the definition of sediment EQS. Therefore, the direct measurement of pore water concentration is regarded as a better option. [Copyright &y& Elsevier]

Presents a study which developed a numerical model called TRANSCAP-1D to stimulate the migration of dissolved contaminants through sediment cap in a marine environment. Mathematical formulation and numerical solutions used; Application of the model to the flood sediments of the Saguenay Fjord; Effect of variable input parameters on the response of the model.

A bioaccumulation model to predict concentrations of s-triazine herbicides in the macroalgae Ulva rigida and in clams Tapes philippinarum has been implemented, calibrated and validated. The model uses input data from a 3D biogeochemical model that provides biomasses in the different compartments, i.e. phytoplankton, zooplankton and bacteria; and from a 3D fate model that provides the herbicides concentrations in the water column as well as in the sediments. Simulated data were compared with experimental data collected during a set of sampling campaigns carried out in 2004 and 2005 in the Sacca di Goro lagoon (Northern Adriatic). The model predicts correctly the concentrations of herbicides measured in Ulva rigida and reproduces with good agreement the values of concentration of herbicides found in clams. Furthermore, the simulated spatial and temporal dynamics in the biota compartment, following those of the water and sediments, are also in agreement with the experimental data. This integrated approach combining biogeochemical, fate and bioaccumulation models provide an overall assessment of the importance of the different environmental compartments and it can also support the testing of different management strategies to improve ecosystem state and functioning. Further research is necessary to elucidate the role and importance of the metabolism of these compounds by clams. [Copyright &y& Elsevier]

Abstract: A non-linear time series analysis technique, recurrence quantification analysis (RQA) based on recurrence plots (RP), is proposed in this paper for the characterization of regime shifts in environmental time series. Its application is illustrated for two case studies: lake eutrophication by excessive phosphorous and the regime shift that occurred in Ringkøbing Fjord when water exchange with the North Sea was modified. The results show that RQA is robust against high noise levels (up to 100%) and may be easily implemented on-line. In addition, oxygen dynamics in a Mediterranean coastal lagoon (Sacca di Goro) is also analyzed and the results compared with surrogate time series with oxygen concentration at saturation. RPs could be used for graphically exploring possible thresholds or breaking points, whereas RQA parameters are suited for locating them. The main drawback is the need of a constant sampling frequency with no gaps, which may be problematic for some environmental time series. [Copyright &y& Elsevier]

Effective use of spatial management in the pelagic realm presents special challenges due to high fish and fisher mobility, limited knowledge and significant governance challenges. The tropical Indian Ocean provides an ideal case study for testing our ability to apply existing data sources to assessing impacts of spatial management on tuna fisheries because of several recent controversial spatial closures. We review the scientific underpinnings of pelagic MPA effects, spatio-temporal patterns of Indian Ocean tuna catch, bycatch and fish movements, and the consequences of these for the efficacy of spatial management for Indian Ocean tropical tuna fisheries. The tropical Indian Ocean is characterized by strong environmental fluctuations, regular seasonal variability in catch, large observed tuna displacement distances, relatively uniform catch-per-unit-effort and bycatch rates over space, and high fisher mobility, all of which suggest significant variability and movement in tropical tuna fisheries that are simply not well adapted to static spatial closures. One possible exception to this overall conclusion would be a large time/area closure east of Somalia. If closed for a significant fraction of the year it could reduce purse-seine bycatch and juvenile tuna catch. Dynamic closures following fish migratory patterns are possible, but more focused information on fish movements will be needed for effective implementation. Fortunately, several recent improvements in conventional fishery management and reporting will likely enhance our ability to evaluate spatial and non-spatial management options in the near future, particularly as pertaining to bycatch species. [ABSTRACT FROM PUBLISHER]

A letter to the editor is presented in response to the article "Giant Marine Reserves Pose Vast Challenges," by C. Pala in the February 8, 2013 issue.