\documentclass[reqno]{amsart} \AtBeginDocument{{\noindent\small {\em Electronic Journal of Differential Equations}, Vol. 2004(2004), No. 108, pp. 1--5.\newline ISSN: 1072-6691. URL: http://ejde.math.txstate.edu or http://ejde.math.unt.edu \newline ftp ejde.math.txstate.edu (login: ftp)} \thanks{\copyright 2004 Texas State University - San Marcos.} \vspace{9mm}} \begin{document} \title[\hfilneg EJDE-2004/108\hfil Persistence and extinction] {Persistence and extinction of single population in a polluted environment} \author[Z. Li, Z. Shuai, K. Wang\hfil EJDE-2004/108\hfilneg] {Zhan Li, Zhisheng Shuai, Ke Wang} % in alphabetical order \address{Zhan Li\hfill\break Department of Mathematics, Key Laboratory for Vegetation Ecology of Education Ministry\\ Northeast Normal University \\ Changchun 130024, China} \email{lizhan1125@hotmail.com \quad Tel: 00 86 631 5689621} \address{Zhisheng Shuai\hfill\break Department of Mathematics, Key Laboratory for Vegetation Ecology of Education Ministry\\ Northeast Normal University \\ Changchun 130024, China} \email{shuaizs@hotmail.com} \address{Ke Wang\hfill\break Department of Mathematics, Harbin Institute of Technology, Weihai 264209, Shandong, China} \email{w\_k@hotmail.com} \date{} \thanks{Submitted January 9, 2004. Published Sept 12, 2004.} \thanks{Supported by the National Natural Science Foundation of China (No.10171010), and by the \hfill\break\indent Key Project on Science and Technology of the Education Ministry of China (No. Key 01061).} \subjclass[2000]{93C15} \keywords{Population dynamics; environment pollution; persistence} \begin{abstract} In this paper, we consider the ODE system corresponding to a diffusive-convective model for the dynamics of a population living in a polluted environment. Sufficient criteria on persistence and extinction of the population are derived. \end{abstract} \maketitle \numberwithin{equation}{section} \newtheorem{theorem}{Theorem}[section] \section{Introduction} Today, the most threatening problem to the society is the change in environment caused by pollution, affecting the long term survival of species, human life style and biodiversity of the habitat. Therefore the study of the effects of toxicant on the population and the assessment of the risk to populations is becoming more important. In the early eighties a deterministic modelling approach to the problem of assessing the effects of a pollutant on an ecological system was proposed by Hallam and his co-workers\cite{h1,h2,h3}. Since then, such models have been the subject of many investigations and improvements. Population-toxicant coupling has been applied in several contexts, including Lotka-Volterra and chemostat-like environments, resulting in ordinary, integro-differential and stochastic models. Usually a qualitative analysis was performed which focuses on the survival or extinction of populations \cite{m1,m2}. All these studies rely on the hypothesis of a complete spatially homogeneous environment. Recently, a first attempt to consider a spatial structure has been carried out in \cite{b2,b3} where a reaction-diffusion model is proposed to describe the dynamics of a living population interacting with a toxicant present in the environment(external toxicant) through the amount of toxicant stored into the bodies of the living organisms(internal toxicant). However, as the authors pointed out, even if the resulting model presents many features which make stimulating its study, such a modelling approach is a rough approximation to the biological phenomena at hand. In 1999, Buonomo et.al. viewed the internal toxicant as drifted by the living population and then, by balance arguments, they derived a PDE system consisting into two reaction diffusion equations coupled with a first order convection equation, and the corresponding ODE system was obtained as well \cite{b1}. This model is the most realistic by now but the analysis of it is so difficult that they only used some analytic and numerical approaches. Obviously, the more clear work is deserved to do. In this paper, we use some new methods to investigate the model made by Buonomo et al. and the conditions of survival and extinction are obtained. \section{The Model} We utilize a modified logistic equation \cite{f1} to model the effect of toxin on single species. We take $n(t)$: concentration of the population biomass $c(t)$: concentration of the toxicant in the environment $z(t)$: concentration of the toxicant in the population. We assume that there is a given(external) toxicant in the environment, and the living organisms absorb into their bodies part of this toxicant so that the dynamics of the population is affected by this(internal) toxicant. Concerning the growth rate of the population we assume that the birth rate is $b(n)=b_0-fn$ and the death rate is $d(n,c)=d_0+\alpha c$, where $b_0$,$d_0$ and $\alpha$ are positive constants. $f$ is assumed to be a non-negative constant. Therefore we assume, in absence of toxicant, a malthusian($f=0$) or a logistic growth rate($f>0$). We can see that if $b_0-d_0-\alpha c\leq 0$, $n(t)$ will be extinct in the end, so we suppose \begin{equation} c<\frac{b_0-d_0}{\alpha}:=c_1.\label{e2.1} \end{equation} We propose the following model governing the system \begin{equation} \label{eM} \begin{gathered} \frac{dn}{dt}=n(b_0-d_0-\alpha c-fn)\\ \frac{dc}{dt}=kz-(r+m+b_0-fn)c\\ \frac{dz}{dt}=-kzn+(r+d_0+\alpha c)cn-hz+u(t). \end{gathered} \end{equation} with initial data $$ n(0)=n_0\geq0;\quad c(0)=c_0\geq0; \quad z(0)=z_0\geq 0. $$ Here $\alpha$ is the depletion rate coefficient of the population due to organismal pollutant concentration. \\ $k$ is the depletion rate of toxicant in the environment due to its intake made by the population. \\ $r$ is the depletion rate of toxicant in the population due to egestion. \\ $m$ is the depletion rate of toxicant in the population due to metabolization processes. \\ $h$ is the depletion rate of the toxicant in the environment. \\ $u$ is the exogen+ous toxicant input rate which is assumed to be a smooth bounded non-negative function of $t$. \section{The conditions of survival and extinction for the population when $u(t)=Q>0$} We now recall the definitions of persistence and extinction. A component $n(t)$ of a given ODE system is said to be persistent if for any $n(0)>0$ it follows that $n(t)>0, t>0$ and $\liminf_{t\to\infty} n(t)>0$. If there exists $\delta>0$ (independent of $n(0)$) such that $n(t)$ is persistent and is bounded and $\liminf_{t\to\infty} n(t)\geq\delta$, then $n(t)$ is said to be uniformly strongly persistent. If there exists $\delta>0$ (independent of $n(0)$) such that $\limsup_{t\to\infty} n(t)\geq\delta$, then $n(t)$ is said to be uniformly weakly persistent. If $\limsup_{t\to\infty} n(t)\leq 0$, then $n(t)$ is said to be extinct. \begin{theorem} \label{thm1} The system \eqref{eM} is uniformly strongly persistent if and only if \[ \alpha kQ0$, such that \begin{equation} n_{k}(t)<2\varepsilon _{k} \quad\mbox{for } t\geq T_{k}. \label{e3.1} \end{equation} From \eqref{e2.1} and \eqref{e3.1} we have $$ \dot{z_{k}}\leq (r+d_0+\alpha c)cn_{k}-hz_{k}+Q\leq(r+b_0)c_12\varepsilon _{k}-hz_{k}+Q \quad\mbox{for } t\geq T_{k}\,. $$ Using the Comparison Theorem we have $$ \limsup_{t\to\infty} z_{k}(t)\leq \frac{c_1(r+b_0)2\varepsilon _{k}+Q}{h}. $$ So for all $\varepsilon>0$, there exists $H_{k}>T_{k}>0$, such that \begin{equation} z_{k}(t)\leq \frac{c_1(r+b_0)2\varepsilon _{k}+Q}{h}+\varepsilon =:\overline{z}_{k} \quad\mbox{for } t\geq H_{k} . \label{e3.2} \end{equation} From \eqref{e3.1} and \eqref{e3.2} we see that \begin{align*} \dot{c_{k}} &\leq k\overline{z}_{k}-(r+m+b_0)c_{k}+f2\varepsilon _{k}c_{k}\\ &= k\overline{z}_{k}-(r+m+b_0-f2\varepsilon_{k})c_{k}~~~for~~ t\geq H_{k}\,. \end{align*} Similarly by the Comparison Theorem and let $\varepsilon\to 0$, we have $$ \limsup_{t\to\infty} c_{k}(t)\leq \frac{kc_1(r+b_0)2\varepsilon _{k}+kQ}{h(r+m+b_0-f2\varepsilon _{k})}\,. $$ Then, for $t\geq H_{k}$, \begin{equation} c_{k}(t)\leq \frac{kc_1(r+b_0)2\varepsilon _{k}+kQ}{h(r+m+b_0-f2\varepsilon _{k})}:=\beta(\varepsilon_{k}). \label{e3.3} \end{equation} Now we consider the first equation of the model \eqref{eM}, from \eqref{e3.3} it is easy to see there exists $S_{k}>H_{k}>0$, such that $$ \dot{n}_{k} \geq n_{k}(b_0-d_0-\alpha \beta(\varepsilon_{k})-fn_{k})~~~for~~ t\geq S_{k}. $$ Using the Comparison Theorem again we have \begin{equation} \liminf_{t\to\infty} n_{k}(t)\geq \frac{b_0-d_0-\alpha\beta(\varepsilon_{k})}{f}. \label{e3.4} \end{equation} By \eqref{e3.4} and the assumption $\limsup_{t\to\infty}n_{k}(t)=\varepsilon _{k}$, we obtain $$ \limsup_{t\to\infty} n_{k}(t)=\varepsilon _{k}\geq \liminf_{t\to\infty} n_{k}(t)\geq \frac{b_0-d_0-\alpha\beta(\varepsilon_{k})}{f}. $$ Let $k\to +\infty$, it follows that $\varepsilon _{k}\to 0$ and $\beta(\varepsilon_{k})\to \frac{kQ}{h(r+m+b_0)}$. Hence, $$ 0\geq \frac{b_0-d_0-\alpha\beta(\varepsilon_{k})}{f}\to \frac{h(b_0-d_0)(r+m+b_0)-\alpha kQ}{fh(r+m+b_0)}\,. $$ That is, $\alpha kQ\geq h(b_0-d_0)(r+m+b_0)$. So there is uniformly weakly persistent if $$ \alpha k Qh( b_{0}-d_{0}) ( r+m+b_{0}) $, $\overline{X}$ is locally asymptotically stable. In particular the system is not uniformly persistent anymore. \begin{theorem} \label{thm2} Consider the system \eqref{eM}. If $Q>\frac{(r+m+b_0)(b_0-d_0)(fh+k(b_0-d_0))}{\alpha kf}$, then the population is extinct. \end{theorem} \begin{proof} From \eqref{e3.1} we know $n(t)\leq n_1$, for $t>t_1$. So from the last equation of the model \eqref{eM} , we can obtain $$ \frac{dz}{dt}>Q-hz-kn_1z \quad\mbox{for } t>t_1. $$ Now we use the Comparison Theorem again, then we have $$ \liminf_{t\to +\infty} z(t) \geq \frac{Q}{h+kn_1}. $$ Let $\varepsilon \to 0$, we have $$ \liminf_{t \to +\infty}z(t)\geq=\frac{fQ}{fh+k(b_0-d_0)}\\:= m_z. $$ That is to say for all $\varepsilon >0,\exists T_1$, such that $z(t)>m_z-\varepsilon$, for all $t>T_1$. From the second equation of the model \eqref{eM} , if $t>T_1$, it is easy to see $$ \frac{dc}{dt}>k(m_z-\varepsilon)-(r+m+b_0)c. $$ Similarly by the Comparison Theorem, $$ \liminf_{t\to +\infty} c(t) \geq\frac{km_z-\varepsilon)}{r+m+b_0}.$$ Let $\varepsilon \to 0$. Then we have \[ \liminf_{t \to +\infty} c(t) \geq \frac{k(m_z}{r+m+b_0} = \frac{kfQ}{(r+m+b_0)(fh+k(b_0-d_0))}\\ =: m_c. \] Then for all $\varepsilon >0$ there exists $T_2>T_1$, such that $c(t)>m_c-\varepsilon$ for all $t>T_2$. Obviously, from the first equation of the model \eqref{eM}, if $t>T_2$, we have $$ \frac{dn}{dt}\frac{(r+m+b_0)(b_0-d_0)(fh+k(b_0-d_0))}{\alpha kf}$, the population will be extinct. \end{proof} \subsection*{Acknowledgements} We thank the anonymous referee for his/her remarks that helped us improving Theorem \ref{thm1}. \begin{thebibliography}{00} \bibitem{b1} B. Buonomo, A. D. Liddo, I. Sgura, \emph{A diffusive-convective model for the dynamics of population-toxocant intentions: some analytical and numerical results}, Math. Biosci. 157(1999), 37-64. \bibitem{b2} B. Buonomo, A. D. Liddo, \emph{On population dynamics in a diffusive polluted environment: a single species model}, Studi Urbinati 1(1997), 69. \bibitem{b3} B. Buonomo, A. D. Liddo, \emph{Large time behaviour of a population-toxicant interaction model}, Rapp.Int. IRMA-CNR. 4/97 1997. \bibitem{h1} T.G. Hallam, C. E. Clark, R. R. Lassiter; \emph{Effects of toxicants on populations: A qualitative approach. I. 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