Anthropogenic stressors, including pollutants, are key evolutionary drivers. It is hypothesized that rapid evolution to anthropogenic changes may alter fundamental physiological processes (e.g., energy metabolism), compromising an organism’s capacity to respond to additional stressors. The Elizabeth River (ER) Superfund site represents a “natural-experiment” to explore this hypothesis in several subpopulations of Atlantic killifish that have evolved a gradation of resistance to a ubiquitous pollutant—polycyclic aromatic hydrocarbons (PAH). We examined bioenergetic shifts and associated consequences in PAH-resistant killifish by integrating genomic, physiological, and modeling approaches. Population genomics data revealed that genomic regions encoding bioenergetic processes are under selection in PAH-adapted fish from the most contaminated ER site and ex vivo studies confirmed altered mitochondrial function in these fish. Further analyses extending to differentially PAH-resistant subpopulations showed organismal level bioenergetic shifts in ER fish that are associated with increased cost of living, decreased performance, and altered metabolic response to temperature stress—an indication of reduced thermal plasticity. A movement model predicted a higher energetic cost for PAH-resistant subpopulations when seeking an optimum habitat. Collectively, we demonstrate that pollution adaption and inhabiting contaminated environments may result in physiological shifts leading to compromised organismal capacity to respond to additional stressors.

Abstract:In this paper, we derive several results related to the long-time behavior of a class of stochastic semilinear evolution equations in a separable Hilbert space H:Here A is a positive self-adjoint operator and B is a bilinear map, and the driving noise L is basically a D(A −1/2 )-valued Lévy process satisfying several technical assumptions. By using a density transformation theorem type for Lévy measure, we first prove a support theorem and an irreducibility property of the Ornstein-Uhlenbeck processes associated to the nonlinear stochastic problem. Second, by exploiting the previous results we establish the irreducibility of the nonlinear problem provided that for a certain γUsing a coupling argument, the exponential ergodicity is also proved under the stronger assumption that B is continuous on H × H. While the latter condition is only satisfied by the nonlinearities of GOY and Sabra shell models, the assumption under which the irreducibility property holds is verified by several hydrodynamical systems such as the 2D Navier-Stokes, Magnetohydrodynamics equations, the 3D Leray-α model, the GOY and Sabra shell models.

We consider the stochastic differential equation (SDE) of the formwhere σ : R d → R d is globally Lipschitz continuous and L = {L(t) : t ≥ 0} is a Lévy process. Under this condition on σ it is well known that the above problem has a unique solution X. Let (P t ) t≥0 be the Markovian semigroup associated to X defined byLet B be a pseudo-differential operator characterized by its symbol q. Fix ρ ∈ R. In this article we investigate under which conditions on σ , L and q there exist two constants γ > 0 and C > 0 such that

Dynamical systems arise in engineering, physical sciences as well as in social sciences. If the state of a system is known, one also knows its properties, and may, e.g., stabilise the system and prevent it from blowing up, or predict its near future. However, the state of a system consists often on internal parameters which are not always accessible. Instead, often only an observation process Y , which is a transformation of the current state, is accessible. Furthermore, a system operates in real environments; hence, itself and its observation are affected by random noise and/or disturbances. So, in reality, the dynamics of the system and the observation are corrupted by noise. The problem of nonlinear filtering is estimating the state of the system X(t) at a given time t > 0 through the data of the observation Y until time t (i.e. {Y (s) : 0 ≤ s ≤ t}).Usually, one considers models where the state process and the observation

We analyse analytic properties of nonlocal transition semigroups associated with a class of stochastic differential equations (SDEs) in R d driven by pure jump-type Lévy processes. First, we will show under which conditions the semigroup will be analytic on the Besov space B m p,q (R d ) with 1 ≤ p, q < ∞ and m ∈ R. Secondly, we present some applications by proving the strong Feller property and give weak error estimates for approximating schemes of the SDEs over the Besov space B m ∞,∞ (R d ).