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Simeon Yurek

Publications and source records attributed to Simeon Yurek.

21 records · Page 2Linked to original sources

Equation-free modeling unravels the behavior of complex ecological systems

Ye et al. (1) address a critical problem confronting the management of natural ecosystems: How can we make forecasts of possible future changes in populations to help guide management actions? This problem is especially acute for marine and anadromous fisheries, where the large interannual fluctuations of populations, arising from complex nonlinear interactions among species and with varying environmental factors, have defied prediction over even short time scales. The empirical dynamic modeling (EDM) described in Ye et al.’s report, the latest in a series of papers by Sugihara and his colleagues, offers a promising quantitative approach to building models using time series to successfully project dynamics into the future. With the term “equation-free” in the article title, Ye et al. (1) are suggesting broader implications of their approach, considering the centrality of equations in modern science. From the 1700s on, nature has been increasingly described by mathematical equations, with differential or difference equations forming the basic framework for describing dynamics. The use of mathematical equations for ecological systems came much later, pioneered by Lotka and Volterra, who showed that population cycles might be described in terms of simple coupled nonlinear differential equations. It took decades for Lotka–Volterra-type models to become established, but the development of appropriate differential equations is now routine in modeling ecological dynamics. There is no question that the injection of mathematical equations, by forcing “clarity and precision into conjecture” (2), has led to increased understanding of population and community dynamics. As in science in general, in ecology equations are a key method of communication and of framing hypotheses. These equations serve as compact representations of an enormous amount of empirical data and can be analyzed by the powerful methods of mathematics.

PNAS

Proposed best modeling practices for assessing the effects of ecosystem restoration on fish

Large-scale aquatic ecosystem restoration is increasing and is often controversial because of the economic costs involved, with the focus of the controversies gravitating to the modeling of fish responses. We present a scheme for best practices in selecting, implementing, interpreting, and reporting of fish modeling designed to assess the effects of restoration actions on fish populations and aquatic food webs. Previous best practice schemes that tended to be more general are summarized, and they form the foundation for our scheme that is specifically tailored for fish and restoration. We then present a 31-step scheme, with supporting text and narrative for each step, which goes from understanding how the results will be used through post-auditing to ensure the approach is used effectively in subsequent applications. We also describe 13 concepts that need to be considered in parallel to these best practice steps. Examples of these concepts include: life cycles and strategies; variability and uncertainty; nonequilibrium theory; biological, temporal, and spatial scaling; explicit versus implicit representation of processes; and model validation. These concepts are often not considered or not explicitly stated and casual treatment of them leads to mis-communication and mis-understandings, which in turn, often underlie the resulting controversies. We illustrate a subset of these steps, and their associated concepts, using the three case studies of Glen Canyon Dam on the Colorado River, the wetlands of coastal Louisiana, and the Everglades. Use of our proposed scheme will require investment of additional time and effort (and dollars) to be done effectively. We argue that such an investment is well worth it and will more than pay back in the long run in effective and efficient restoration actions and likely avoided controversies and legal proceedings.

Ecological Modelling

Simulating mechanisms for dispersal, production and stranding of small forage fish in temporary wetland habitats

Movement strategies of small forage fish (<8 cm total length) between temporary and permanent wetland habitats affect their overall population growth and biomass concentrations, i.e., availability to predators. These fish are often the key energy link between primary producers and top predators, such as wading birds, which require high concentrations of stranded fish in accessible depths. Expansion and contraction of seasonal wetlands induce a sequential alternation between rapid biomass growth and concentration, creating the conditions for local stranding of small fish as they move in response to varying water levels. To better understand how landscape topography, hydrology, and fish behavior interact to create high densities of stranded fish, we first simulated population dynamics of small fish, within a dynamic food web, with different traits for movement strategy and growth rate, across an artificial, spatially explicit, heterogeneous, two-dimensional marsh slough landscape, using hydrologic variability as the driver for movement. Model output showed that fish with the highest tendency to invade newly flooded marsh areas built up the largest populations over long time periods with stable hydrologic patterns. A higher probability to become stranded had negative effects on long-term population size, and offset the contribution of that species to stranded biomass. The model was next applied to the topography of a 10 km × 10 km area of Everglades landscape. The details of the topography were highly important in channeling fish movements and creating spatiotemporal patterns of fish movement and stranding. This output provides data that can be compared in the future with observed locations of fish biomass concentrations, or such surrogates as phosphorus ‘hotspots’ in the marsh.

Ecological Modelling