S. Lan Smith

End-To-End Models for the Analysis of Marine Ecosystems: Challenges, Issues, and Next Steps

Abstract There is growing interest in models of marine ecosystems that deal with the effects of climate change through the higher trophic levels. Such end-to-end models combine physicochemical oceanographic descriptors and organisms ranging from microbes to higher-trophic-level (HTL) organisms, including humans, in a single modeling framework. The demand for such approaches arises from the need for quantitative tools for ecosystem-based management, particularly models that can deal with bottom-up and top-down controls that operate simultaneously and vary in time and space and that are capable of handling the multiple impacts expected under climate change. End-to-end models are now feasible because of improvements in the component submodels and the availability of sufficient computing power. We discuss nine issues related to the development of end-to-end models. These issues relate to formulation of the zooplankton submodel, melding of multiple temporal and spatial scales, acclimation and adaptation, behavioral movement, software and technology, model coupling, skill assessment, and interdisciplinary challenges. We urge restraint in using end-to-end models in a true forecasting mode until we know more about their performance. End-to-end models will challenge the available data and our ability to analyze and interpret complicated models that generate complex behavior. End-to-end modeling is in its early developmental stages and thus presents an opportunity to establish an open-access, community-based approach supported by a suite of true interdisciplinary efforts.

Modeling the transport and reaction of trace metals in water‐saturated soils and sediments

A model has been formulated of the equilibrium speciation, kinetic reaction, and transport of trace metals in the presence of biodegradation of organic substrates in saturated porous media. Kinetics of various processes (biodegradation, chemical reactions, and precipitation and dissolution of minerals) together with transport processes (advection, bioturbation, and diffusive/dispersive mixing) are quantified in a set of coupled mass balance equations (for the organic substrate, electron acceptors, reduced species, and trace metals). These steady state, one-dimensional equations are discretized using a second-order-accurate finite difference approximation. A pE is estimated at each node in the domain on the basis the concentrations calculated and the half reaction for the dominant terminal electron acceptor at that location. The dynamic model is coupled iteratively to a modified version of the U.S. Environmental Protection Agencys MINTEQA2, which calculates equilibrium chemical speciation (including aqueous speciation, adsorption, and precipitation of minerals) at each node of the domain. The primary dependent variables are the total dissolved concentrations of the aqueous species together with the solid concentrations of the minerals. To demonstrate that this formulation can simulate biodegradation using reaction rates consistent with published values, simulations are compared to data from the sediment pore waters of a small lake. Simulations are presented of the transport and reaction of arsenic in lake sediments to illustrate how this model can be used to evaluate trends in trace metal mobility as affected by various water quality parameters through their influence on the biogeochemistry of natural systems.

Phytoplankton size-diversity mediates an emergent trade-off in ecosystem functioning for rare versus frequent disturbances

Biodiversity is known to be an important determinant of ecosystem-level functions and processes. Although theories have been proposed to explain the generally positive relationship between, for example, biodiversity and productivity, it remains unclear which mechanisms underlie the observed variations in Biodiversity-Ecosystem Function (BEF) relationships. Using a continuous trait-distribution model for a phytoplankton community of gleaners competing with opportunists, and subjecting it to differing frequencies of disturbance, we find that species selection tends to enhance temporal species complementarity, which is maximised at high disturbance frequency and intermediate functional diversity. This leads to the emergence of a trade-off whereby increasing diversity tends to enhance short-term adaptive capacity under frequent disturbance while diminishing long-term productivity under infrequent disturbance. BEF relationships therefore depend on both disturbance frequency and the timescale of observation.

Untangling the uncertainties about combined effects of temperature and concentration on nutrient uptake rates in the ocean.

[1] I show that assumptions about how uptake rates depend on concentration strongly impact the interpretation of field observations, specifically with respect to the combined effects of temperature, T, and nitrate concentration, [NO 3 ], on nitrate uptake. The standard assumption that maximum uptake rate, V max , is independent of ambient nutrient concentration, S a , contrasts with the prediction of the recently developed Optimal Uptake kinetics that V max should increase hyperbolically with S a . Assuming Arrhenius T dependence, I fit the respective equations to field observations of chlorophyll-specific V max , T and [NO 3 ]. The inferred sensitivity to T differs by a factor of two. Considerable uncertainty therefore remains about the T dependence of uptake rates, and therefore about biological production and biogeochemical cycles. Given that both climate change and anthropogenic nutrient inputs are altering the relationship between T and nutrients in the ocean, these uncertainties limit our understanding of the direct effects and associated feedbacks.

Micro-scale variability enhances trophic transfer and potentially sustains biodiversity in plankton ecosystems

We develop moment closure approximations to represent micro-scale spatial variability in the concentrations of nutrients (N), phytoplankton (P) and zooplankton (Z) in an NPZ model, which we apply to examine the impact of different levels of micro-scale variability on both ecosystem dynamics and trophic transfer. Accounting explicitly for both the mean-field and fluctuating components of each prognostic variable in the NPZ model yields different dynamics for the mean-field concentrations, as well as lower phytoplankton biomass and greater zooplankton biomass, compared to the conventional NPZ model without micro-scale variability. The biomass of zooplankton consistently increases with increasing total micro-scale variability, and a minimum threshold of such variability is required for the existence of stable steady state solutions in the NPZ closure model. Compared to the conventional NPZ model, the domain of parameter space over which stable solutions exist is larger than for the NPZ closure model, and this stable domain widens with increasing total variability. The latter result suggests that natural systems with greater micro-scale variability may have the potential to sustain greater biodiversity. We find that with the NPZ closure model: (1) the stability domains increases with micro-scale variability, (2) increase of the level of total micro-scale variability enhances trophic transfer, i.e. increases the biomass of zooplankton, and (3) the coefficient of variation (CVP) of phytoplankton increases with micro-scale variability.

Modeling the Combined Effects of Physiological Flexibility and Micro-Scale Variability for Plankton Ecosystem Dynamics

Plankton are microscopic organisms that constitute the sustaining base of food chains in the ocean. Various models have been developed using equations to study their important roles in marine ecology and chemistry. Such models typically assume that plankton respond to changing environmental conditions according to simplistic response equations, and that they experience uniform local conditions. However, experiments and observations have revealed both of those assumptions to be false. We describe recent approaches for modeling the observed flexible physiological response and micro-scale heterogeneity of plankton and introduce preliminary findings concerning their combined effects on plankton ecosystem dynamics.