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这是一个关乎社会essay的问题。关于出生率下降的问题，出生率正在下降，在发达国家。有一个简单的原因，现在的年轻人崇尚自由，不想要要孩子”而且这种情况已经到了一定的程度，你同意这种观点吗？相关阅读资料和证据支持你的论点。
"Birth rates are falling in developed countries. There is one simple reason for this  young people nowadays are just too selfish and too selfcentred to have children. And this is particularly true of women". To what extent do you agree with this view? Support your argument with relevant readings and evidence.
Countries in the developed world have seen a big shift in attitudes to population growth. Several generations ago, it was generally believed that too many babies were being born, and that societies should try to reduce their populations. Nowadays, however, the concern is the reverse  that birthrates are falling too low and that urgent action is needed to encourage people to have more children. But what are the causes of this trend? And how much are the attitudes and lifestyles of young people to blame? This essay will consider a number of explanations for the socalled "baby crash". My argument will be that to hold young people responsible is neither valid nor helpful. The best explanation, I believe, is to be found in the condition of increased economic insecurity faced by the young.
The birth rate has fallen dramatically in many parts of the world. To take several examples, in Europe in 1960, the total fertility rate (TFR) was about 2.6 births per female, but in 1996 it had fallen to 1.4 (Chesnais, 1998). In many Asian countries, similar declines have been experienced. Japan now has a birthrate of only about 1.3, and Hong Kong's has fallen to below 1.0 (Ichimura and Ogawa, 2000). A TFR of below 2.0 means that a country's population is not replaced, and thus there is a net population decline. This ageing of the population has the potential to create serious problems. Fewer children being born means that in the long term, a smaller proportion of the populace will be economically productive, whilst a larger proportion will be old and economically dependent  in the form of pension, health care and other social services. Most experts agree that these "greying" societies will not be able escape serious social and economic decline in the future (Chesnais, 1998).
So what are the causes of this trend and what can be done to stop it? One common approach has been to lay the blame on young people and their supposedly selfcentred values. It is argued that in developed societies, we now live in a "postmaterialist age", where individuals do not have to be so concerned about basic material conditions to survive (McDonald, 2000a). Thus people, especially the young, have become more focussed on the values of selfrealisation and the satisfaction of personal preferences, at the expense of traditional values like raising a family. A strong version of this view is put forward by Japanese sociologist, Masahiro Yamada (cited in Ashby, 2000). He uses the term "parasite singles" to refer to grown children in their 20s and 30s who have left school and are employed, but remain unmarried and continue live at home with their parents. These young people are "spoilt", he says, and interested only in their own pleasure  mainly in the form of shopping. According to Yamada, it is this focus on self, more than any other factor, that is responsible for Japan's languishing birth rate (Ashby, 2000). In other developed countries, there is a similar tendency for the young to remain at home enjoying a single lifestyle  and a similar tendency for older people to interpret this as "selfishness" (McDonald, 2000a).
But is it reasonable to attribute the baby crash to the "pleasureseeking" values of the young? The problem with this view is that whenever young people are surveyed about their attitudes to family, not only do they say they want to have children, they also express preferences for family sizes that are, on average, above the replacement level (McDonald, 2000a). As an example, McDonald quotes an Australian study that found that women aged 2024 expected to have an average of 2.33 children in their lifetime. Findings like this suggest that the values of the young are not at all incompatible with the idea of having a family. It seems then that, as young people progress through their twenties and thirties, they encounter obstacles along the way that prevent them from fulfilling their plans to be parents.
Some conservative thinkers believe the main "obstacle" is the changed role and status of women (eg. Norton, 2003). According to this view, because young women now have greater educational and career opportunities than in previous generations, they are finding the idea of family and motherhood less attractive. Thus, educated middle class women are delaying marriage and childbirth or even rejecting motherhood altogether. It is claimed that women's improved status  which may be a good thing in itself  has had the unfortunate consequence of threatening population stability.
But there are several problems with this argument. For one, the lowest TFRs in Europe are found in Spain and Italy (around 1.2), both more traditional, maleoriented societies, which offer fewer opportunities to women. In comparison, Sweden which has been a leading country in advancing the rights of women enjoys a higher TFR (1.6 in 1996)  even though it is still below replacement. Chesnais (1998: p. 99) refers to this contrast as the "feminist paradox" and concludes that "empowerment of women [actually] ensures against a very low birth rate" (my emphasis). Another problem with trying to link improved education levels for women to low birth rates is that fertility in developed countries seems to be declining across all education and class levels. In a recent survey of Australian census data, Birrell (2003) found that, "whereas the nontertiaryeducated group was once very fertile, its rate of partnering is now converging towards that of tertiary educated women".
We can summarise the discussion to this point as follows:
These conclusions suggest that there must be something else involved. Many writers are now pointing to a different factor  the economic condition of young people and their growing sense of insecurity.
Peter McDonald (2000a) in his article 'Low fertility in Australia: Evidence, causes and policy responses' discusses some of the things that a couple will consider when they are thinking of having a child. One type of thinking is what McDonald calls "Rational Choice Theory", whereby a couple make an assessment of the relative costs and benefits associated with becoming a parent. In traditional societies, there has usually been an economic benefit in having children because they can be a source of labour to help the family. In developed societies, however, children now constitute an economic cost, and so, it is argued, the benefits are more of a psychological kind  for example, enjoying the status of being a parent, having baby who will be fun and will grow up to love you, having offspring who will carry on the family name etc. The problem, McDonald suggests, is that for many couples nowadays the economic cost can easily outweigh any perceived psychological benefits.
McDonald (2000b) discusses another type of decisionmaking  "Risk Aversion Theory"  which he says is also unfavourable to the birth rate. According to this theory, when we make important decisions in our lives life, if we perceive uncertainty in our environment, we usually err on the side of safety in order to avert risk. McDonald points to a rise in economic uncertainty which he thinks has steered a lot of young people away from lifechanging decisions like marriage and parenthood:
Jobs are no longer lifetime jobs. There is a strong economic cycle of booms and busts. Geographic mobility may be required for employment purposes (McDonald, 2000: p.15).
Birrell (2003) focuses on increased economic uncertainty for men. Referring to the situation in Australia, he discusses men's reluctance to form families in terms of perceived costs and risks:
Many men are poor  in 2001, 42 per cent of men aged 2544 earnt less than $32,000 a year. Only twothirds of men in this age group were in fulltime work. Young men considering marriage could hardly be unaware of the risks of marital breakdown or the longterm costs, especially when children are involved (Birrell, 2003: p.12).
And Yuji Genda (2000) in Japan, responding to Yamada's analysis of "parasite singles", argues that the failure of young Japanese to leave home and start families is not due to selfindulgence, but is an understandable response to increasingly difficult economic circumstances. Genda (2000) notes that it is the young who have had to bear the brunt of the decade long restructuring of the Japanese economy, with youth unemployment hovering around 10% and a marked reduction in secure fulltime jobs for the young.
Young people around the world seem to have an increasing perception of economic uncertainty and contemplate something their parents would have found impossible  a decline in living standards over their lifetime. According to a 1990 American survey, two thirds of respondents in the 1829 age group thought it would be more difficult for their generation to live as comfortably as previous generations (cited in Newman, 2000: p.505). Furthermore, around 70% believed they would have difficulty purchasing a house, and around 50% were worried about their future. Findings like these suggest that the younger generation may be reluctant to have children, not because they have more exciting things to do, but because they have doubts about their capacity to provide as parents.
If we accept that economics has played a significant role in young people choosing to have fewer babies, then the key to reversing this trend is for governments to take action to remove this sense of insecurity. A number of policy approaches have been suggested. Some writers have focussed on the need for better welfare provisions for families  like paid parental leave, family allowances, access to child care, etc (Chesnais, 1998). Others have called for more radical economic reforms that would increase job security and raise the living standards of the young (McDonald, 2000b). It is hard to know what remedies are needed. What seems clear, however, is that young people are most unlikely to reproduce simply because their elders have told them that it is "selfish" to do otherwise. Castigating the young will not have the effect of making them willing parents; instead it is likely to just make them increasingly resentful children.
Ashby, J. (2000). Parasite singles: Problem or victims? The Japan Times. 7/04/02.
Birrell, B. (2003). Fertility crisis: why you can't blame the blokes. The Age 17/01/03 p. 14.
Chesnais, JC. (1998). Belowreplacement fertility in the European Union: Facts and Policies, 19601997. Review of Population and Social Policy, No 7, pp. 83101.
Genda, Y. (2000). A debate on "Japan's Dependent Singles", Japan Echo, June, 2000, pp. 4756
Ichimura, S. and N. Ogawa (2000). Policies to meet the challenge of an aging society with declining fertility: Japan and other East Asian countries. Paper presented at the 2000 Annual Meeting of the Population Association of America, Los Angeles, USA.
McDonald, P. (2000a). Low fertility in Australia: Evidence, causes and policy responses. People and Place, No 8:2. pp 621.
Available: http://elecpress.monash.edu.au/pnp/free/pnpv8n1/ [Accessed 10/5/03]
McDonald, P. (2000b). The "toolbox" of public policies to impact on fertility  a global view. Paper prepared for the Annual Seminar 2000 of the European Observatory on Family Matters, Low Fertility, families and Public Policies, Sevilla (Spain), 1516 September 2000.
Norton, A. (2003). Student debt: A HECS on fertility? Issue Analysis No 3. Melbourne: Centre for Independent Studies.
Newman, D. (2000). Sociology: Exploring the architecture of everyday life. California: Pine Forge.
这篇作文的题目是关于课外体育活动。利用跑步锻炼这个题材，作者阐述了自己对人生现实的认知，充满了积极向上的期待。
I'M GOING RUNNING TODAY. I am not concerned about my calorie consumption for the day, nor am I anxious to get in shape for the winter season. I just want to go running。
I used to dislike running. "If you don't win this game, you're all running five miles tomorrow," the field hockey coach used to warn, during those last days of October when the average temperature seemed to be decreasing exponentially. And so, occasionally, my griefstricken team would run numerous miserable laps around the fields. At the end of these excursions, our faces and limbs would be numb, and we would all have developed those notorious flulike symptoms; but the running made us better in the long run, I suppose. Nevertheless, I counted down the days until the end of the field hockey season, vowing never to put on a pair of running shoes again. Then I surprised myself by signing up for outdoor track in the second half of sophomore year. I was foolish to have believed that I could ever escape this insidious and magnetic addiction。
Anyone would have thought that I'd be off the team in a few days, but the last week of January caught me splashing through puddles of melted ice, and February winds nearly blew me off the track. I looked forward to practices this time around, to the claps and the persistent cheers of my fellow trackies. I was feeling a "runner's high" spurred by the endorphins released by exercise. But to attribute my affinity for running solely to chemistry diminishes the personal importance that running has for me。
I like running—in the cool shade of the towering oak trees, and in the warm sunlight spilling over the horizon, and in the drops of rain falling gently from the clouds. Certain things become clear to me when I'm running—only while running did I realize that "hippopotami" is possibly the funniest word in the English language, and only while running did I realize that the travel section of The York Times does not necessarily provide an accurate depiction of the entire world. Running lends me precious moments to contemplate my life: while running I find time to dream about changing the world, to think about recent death of a classmate, or to wonder about the secret to college admission
Running is the awareness of hurdles between me and the finish line; running is the desire to overcome them. Running is putting up with aches and pains, relishing the knowledge that, in the end, I will have built strength and endurance. Running is the instant clarity of vision with which I can see my future just one hundred yards in the distance; it is the understanding that these crucial steps will determine victory or defeat。
Running is not the most important thing in the world to me, but it is what fulfills me when time permits. And right now, before the sun goes down, I like to take advantage of the road that lies ahead。
解析：
要完全理解这篇作文，有必要提到据说是比尔·盖茨送给年轻人的十一条忠告：
1. 生活是不公平的，你要去学会适应它；
2. 这世界不会在意你的自尊，这世界指望你在自我感觉良好之前先要有所成就；
3. 高中刚毕业后你不会一下就拿到年薪六万美金的职位，你也不会很快成为拥有车载电话的公司副总，这些都要你自己挣得；
4. 如果你认为你的老师严厉，等你有了老板后再比较，老板可不是终身的；
5. 翻烤汉堡包并不有损你的尊严。你的长辈们用另一个词来描述这份工作，他们称之为机遇；
6. 如果你搞砸了，那不是你父母的错，不要只会发牢骚，要学会吸取教训；
7. 在你出生之前，你的父母并非像现在这样乏味。他们变成今天这个样子是因为这些年来他们一直在为你付账单，给你洗衣服，听你大谈你是如何的酷。在你大谈拯救雨林以免遭受你父母辈的寄生虫的危害时，先把你自己衣橱里的跳蚤除去；
8. 你的学校也许已经不再分优等生和劣等生，但生活却仍在划分；有些学校已经废除了不及格并给你想要多少就多少的机会让你得到正确的答案。但在现实生活中，却完全不同；
9. 生活不分学期，你并没有暑假可以休息，也没有几个人乐于帮你发现自我。你得用你自己的时间去发现；
10. 电视并不是真实的生活，在现实生活中，人们得离开咖啡屋去干自己的工作；
11. 善待那些看似怪异的人，很有可能有一天你会不得不为他们打工。
美国的大学教育是普通教育，培养有一技之长、对社会有用并且能适应社会的人。现实社会，不可避免会有很多不公平的地方，要成功，需要有顽强的心理素质。名牌大学对学生未来的发展期望很高，对学生承受压力、正视挫折的能力非常看重。很多大学的命题作文直接或间接地考察学生面对人生逆境的表现；而一个聪明的学生也会利用机会展示自己面对挑战的勇气和进取心。
在这篇作文里，作者开始就提到了自己早年在曲棍球队的经历：一个粗暴有虐待倾向的教练和惩罚性的长跑。尽管心里很不乐意，作者并没有放弃，反而以一种适应的态度去对待并最终迷上了这项运动。径赛队同伴的鼓励，让我们看到了作者珍惜友爱和社会的温情；作者的感悟，让我们既看到了作者走向社会的心理准备，又充满了积极的人生向往。一般的作文要求500单词左右，这篇文章共503单词，在有限的空间，包含了磨难，毅力，关怀，理解，憧憬。全文词汇优雅丰富，修辞巧妙，用了很多排比句，画面感非常强，感染力也非常强。在具体写作技巧上，有二点值得一提：
1. 使用了不少科学词汇，如指数般(exponentially)，内啡肽(endorphin)，爱好(affinity)，这些词汇的应用显然有利于叩击麻省理工学院的大门。
2. 巧妙甚至狡猾地使用了幽默。幽默是个双刃剑，往往容易弄巧成拙，一般人在作文里会尽量避免。然而，作者却大胆地调侃道：跑步时，会去猜想大学招生的秘密 这简直是在向正在阅读此作文的招生人员叫阵！但是，说这句话的时候，招生的人应该已经为其经历和毅力所触动，而且前面谈到河马单词，已经把作文的节奏调得轻松，这句话会让招生人员会心一笑，拉近了彼此的距离。而随后梦幻般的紧凑道白，为这篇作文留下了非常美妙的收尾。
Lauren 是个可男可女的名字，但从第一段谈论控制体重保持身材就可看出是个女孩。的确，这篇文章透着一股女孩气，精灵机警，如同金庸小说里的某位人物。
本文建立了数学模型用以研究具有种群内控制的时滞两种群竞争生态系统,并讨论了成熟时滞以及捕获努力对种群动力学的影响。研究了三个非负平衡点以及唯一正平衡点存在的条件。分析了系统解的正定性与有界性。通过分析对应的特征方程,研究了系统在非负平衡点以及正平衡点附近的局部稳定性。利用迭代算法研究了非负平衡点的全局稳定性。通过建立适当Lypunov函数,研究了唯一正平衡点的全局稳定性。最后,通过数值仿真验证本文研究结果Dynamics Analysis in a Delayed
TwoSpecies
Competition Model with Harvest Eﬀort and
Nonlinear Intraspeciﬁc Regulation
LIU Chao12, WANG XiaoMin3, Yue WenQuan4
1 Institute of Systems Science, Northeastern University, Shenyang 110004
2 State Key Laboratory of Integrated Automation of Process Industry, Northeastern
University, Shenyang, 110819
3 School of Mathematics and Statistics, Northeastern University at Qinhuangdao,
Qinhuangdao, 066004
4 Hebei Academy of Agricultural and Forestry Sciences, Shijiazhuang, 050000
Abstract: In this paper, a mathematical model is established to investigate interaction and
coexistence mechanism of twospecies competition ecosystem with nonlinear intraspeciﬁc
regulation. The combined dynamic eﬀects of maturation delay and harvest eﬀort on
population dynamics are discussed. Conditions for existence of three nonnegative boundary
equilibria and a unique interior equilibrium are investigated. Positivity and boundedness of
solutions are analytically studied. By analyzing associated characteristic equation, local
stability of the proposed model around nonnegative boundary equilibrium and interior
equilibrium is discussed, respectively. Furthermore, global stability of the nonnegative
boundary equilibrium is investigated based on an iterative technique. By constructing an
appropriate Lyapunov functional, global stability of the unique interior equilibrium is also
discussed. Numerical simulations are carried out to show consistency with theoretical analysis.
Key words: Operations research and control theory; maturation delay, harvest eﬀort,
nonlinear intraspeciﬁc regulation, global stability analysis
0 Introduction
Competition is an interaction among competing species, in which the ﬁtness of one is
lowered by the presence of another species within ecosystem. Generally, competition is very
important in determining the characteristics of species, and there are two types of competition,
intraspeciﬁc competition and interspeciﬁc competition [1, 2].
Intraspeciﬁc competition is an interaction in population ecology, whereby members of the
same species compete for limited resources. When resources are limited, an increase in popula
tion size reduces the quantity of resources available for each individual, reducing the per capita
ﬁtness in the population. As a result, the growth rate of a population slows as intraspeciﬁc
competition becomes more intense, making it a negatively density dependent process [1, 2]. In
the natural world, intraspeciﬁc competition phenomenon can be observed in a variety of ways.
Bird songs are often signals to other birds that they are not welcome in that area, which are
used to defend territories that contain breeding areas, shelter, and food. Many wild canine and
feline species mark their territories with scent, which tells other members of the same species
in that area that they have claimed the territory and all of the resources within it. Intraspeciﬁc
competition for mates can be quite dramatically observed through ornamental features. For
example, male peacocks display beautiful plumage to attract females. Male deer ﬁght each
other for mates with their large antlers; the larger set of antlers usually wins this competition
[3, 4, 5].
Interspeciﬁc competition refers to the competition between two or more species for some
limiting resource. This limiting resource can be food or nutrients, space, mates, nesting sites,
anything for which demand is greater than supply. When one species is a better competi
tor, interspeciﬁc competition negatively inﬂuences the other species by reducing population
 2 
sizes and/or growth rates, which in turn aﬀects population dynamics of the competitor [1, 4].
Generally, interspeciﬁc competition has the potential to alter populations, communities and
the evolution of interacting species. On an individual organism level, interspeciﬁc competi
tion can occur as interference or exploitative competition. There are some vivid interspeciﬁc
competition examples in the natural world, if a tree species in a dense forest grows taller than
surrounding tree species, it is able to absorb more of the incoming sunlight. However, less
sunlight is then available for the trees that are shaded by the taller tree. Cheetahs and lions
can also be in interspeciﬁc competition, since both species feed on the same prey, and can be
negatively impacted by the presence of the other because they will have less food [3, 4, 5].
In the 1920s, the dynamic impacts of intraspeciﬁc and interspeciﬁc competition on pop
ulation dynamics have been discussed in [6, 7]. Under some necessary simpliﬁed assumptions
that there are not migration, and the carrying capacities and competition coeﬃcients for both
species are constants, Lotka and Volterra propose a mathematical model in [6, 7], which takes
the following form,
{
x˙1(t) = x1(t)(b1− a11x1(t) − a12x2(t)),
x˙2(t) = x2(t)(b2− a22x2(t) − a21x1(t)),
where xi(t) (i = 1, 2) represents population density of the competing ith species at time t,
respectively. bi(i = 1, 2) denotes the birth rate of the corresponding species; aij(i, j =
1, 2, i̸= j) is the corresponding linear reduction of the ith species’ rate growth by interspeciﬁc
competition, the j th species. aii(i = 1, 2) stands for the corresponding linear reduction of the
ith species’ rate growth by intraspeciﬁc competition. It should be noted that model (1) combines
the eﬀects of each species on the other and creates a theoretical prediction of interactions that
can be used to understand how diﬀerent factors aﬀect the outcomes of competitive interactions.
However, a variety of factors, which may aﬀect the outcome of competitive interactions and
dynamics of one or both populations, are not considered in the model (1). In the 1970s, Gilpin
and Ayala [8, 9, 10] conducted experiments on drosophila dynamics to test validity of ten
competition models. One of the models accounting for the experimental results is given as
follows:
{
˙1(t) = x1(t)(b1− a11xθ11(t) − a12x2(t)),
˙2(t) = x2(t)(b2− a22xθ22 (t) − a21x1(t)),
where model (2) is an extension of the LotkaVolterra’s model, and estimations of θi(i = 1, 2)
for drosophila in the literature [8, 9, 10] suggest that θiis typically less than one.
Along with this line of research on model (2), persistence and asymptotical stability analysis
of competing species are studied in recent decades, which can be found in [11, 12, 13, 14, 15, 16]
and references therein. By constructing appropriate Lyapunov function, Goh et al. [11] inves
tigate global stability of the proposed model with θ1≥ 1, θ2≥ 1. Zhou et al. [12] and Fan et al.
[13] discuss global stability of the proposed model with θ1≥ 1, θ2≥ 1 and θ1≤ 1, θ2≤ 1. Chen
 3 
et al. [15] propose a discrete GilpinAyala type multispecies competition model. For general
nonautonomous case, suﬃcient conditions which ensure permanence and global stability of the
proposed model are obtained; For periodic case, suﬃcient conditions which ensure the existence
of an unique globally stable positive periodic solution are obtained. Liao et al. [16] propose
a discrete multispecies general GilpinAyala competition predator prey model. By using new
diﬀerence inequality and developing the analysis technique of Chen [14], suﬃcient conditions
are established for permanence and the global stability in [16]. Dynamic eﬀect of impulsive
control and asymptotic stability analysis on GilpinAyala competition model are investigated
in [17, 18, 19, 20]. Permanence and extinction of stochastic nonautonomous GilpinAyala type
competition model with delays are investigated in [21, 22, 23, 24, 25]. A delayed nonautonomous
nspecies GilpinAyala type competition system is proposed in [21], which is more general and
more realistic then classical LotkaVolterra type competition model. M. Vasilova [23] studies
the stochastic GilpinAyala competition model with an inﬁnite delay, veriﬁes that the environ
mental noise included in the model does not only provide a positive global solution and certain
asymptotic results regarding a large time behavior are obtained. A stochastic GilpinAyala
predatorprey model with time dependent delay is studied in [24], and suﬃcient conditions for
existence of a global positive solution of the considered model are obtained. Furthermore, suf
ﬁcient criteria for extinction of species for a special case of the considered system are given. In
[25], the nonautonomous stochastic GilpinAyala competition model with timedependent delay
is considered. Existence and uniqueness of the global positive solution and various properties of
that solution are proved in [25]. By considering the stage structure of competing species within
competition ecosystem, model (2) is extended by incorporating maturation delay of both two
competing species, which can be found in [18, 26, 27]. In the work done in [27], the stage
structured GilpinAyala competition model of discrete delays are discussed as follows:
{
x˙1(t) = b1e−d1τ1x1(t − τ1) − a11x1+1 θ1(t) − a12x1(t)x2(t),
x˙2(t) = b2e−d2τ2x2(t − τ2) − a22x1+2 θ2(t) − a21x1(t)x2(t),
(3)
where τi, i = 1, 2 denotes the maturation delay of species xi(t), respectively. The term e−diτi
denotes the corresponding surviving rate of species i during its maturation duration from
immature to mature stage. Other parameters share the same interpretations mentions in model
(2). The global asymptotical stability criteria for the coexistence equilibrium as well as the
excluding equilibria are established in [27].
It is well known that many species within competition ecosystem are of agricultural and
medical utilization, which are mostly harvested and sold with the purpose of obtaining the
economic interest [4]. It motivates the introduction of commercial harvesting into mathematical
model and dynamic analysis of harvest eﬀort on population dynamics are discussed in [1, 3, 4].
Although there are much progress on GilpinAyala competing model, such models are discussed
in the sense that the above work ignore commercial harvesting, which can not vividly reﬂect
complex biological phenomena from harvested competition ecosystem. Since harvesting has
a strong impact on the dynamic evolution of a population, it is necessary to investigate the
dynamic eﬀect of harvesting on GilpinAyala competing population dynamics. Based on the
above analysis, model (3) is extended by incorporating harvest eﬀort on two competing species
in this paper, and the combined dynamic eﬀect of harvest eﬀort and maturation delays on
population dynamics will be discussed in this paper.
The rest section of this paper is organized as follows: a delayed twospecies competition
model with harvest eﬀort and nonlinear intraspeciﬁc regulation is established in the second
section. Conditions for existence of three nonnegative boundary equilibria and a unique interior
equilibrium are analytically investigated. Positivity and boundedness of solutions of model are
also studied. In the third section, local stability of the proposed model around nonnegative
boundary equilibrium and interior equilibrium is discussed, respectively. In the fourth section,
global stability of the nonnegative boundary equilibrium is investigated based on an iterative
technique. By constructing an appropriate Lyapunov functional, global stability of the unique
interior equilibrium is also discussed. In the ﬁfth section, numerical simulations are given
to support the theoretical ﬁndings obtained in this paper. Finally, this paper ends with a
conclusion.
1 Model Formulation
By incorporating harvest eﬀort into model (3), a delayed twospecies competition model
with harvest eﬀort and nonlinear intraspeciﬁc regulation is established in this section. Further
more, conditions for existence of three nonnegative boundary equilibria and a unique interior
equilibrium are analytically investigated. Positivity and boundedness of solutions of model are
also studied. In this paper, the model is proposed based on the following hypotheses.
(H1) xi(t) (i = 1, 2) represents population density of the competing ith species at time t,
respectively. bi(i = 1, 2) denotes the birth rate of the corresponding species; aij(i, j =
1, 2, i̸= j) is the corresponding linear reduction of the ith species’ rate growth by its
competitor, the jth species. aii(i = 1, 2) is the corresponding linear reduction of the ith
species’ rate growth by the same species, the ith species.
(H2) τi, i = 1, 2 denotes the maturation delay of species i, respectively. The term e−diτi
denotes the corresponding surviving rate of species i during its maturation duration from
immature to mature stage.
(H3) E1≥ 0 and E2≥ 0 denotes harvest eﬀort on competing species x1(t) and x2(t), respec
tively. q1E1x1(t) and q2E2x2(t) represents the catch of species x1(t) and x2(t), respec
tively. q1and q2represents the catchability coeﬃcients of harvest eﬀort on species x1(t)
and x2(t), respectively.
http://www.paper.edu.cn
According to (H1)(H3), a delayed twospecies competition model with harvest eﬀort and
nonlinear intraspeciﬁc regulation is proposed as follows:
{
x˙1(t) = b1e−d1τ1 x1(t − τ1) − a11x1+1 θ1(t) − a12x1(t)x2(t) − q1E1x1(t),
x˙2(t) = b2e−d2τ2x2(t − τ2) − a22x1+2 θ2(t) − a21x1(t)x2(t) − q2E2x2(t).
In this paper, model (4) will be discussed with θ1≥ 1, θ2≥ 1 and θ1< 1, θ2< 1 under
the following initial conditions:
{
x1(t) = ϕ1(t) > 0, −τ1≤ t ≤ 0,
x2(t) = ϕ2(t) > 0, −τ2≤ t ≤ 0.
Theorem 1. All solutions of model (4) with initial conditions (5) are positive for allt > 0.
Proof.Firstly, we show that x1(t) > 0 for all t > 0. If x1(t) ≤ 0 for all t > 0, then it follows
from initial conditions (5) that there exists
t0= inf{t > 0x1(t) = 0}.
According to initial conditions (5) and deﬁnition of t0, it is easy to show that x˙1(t0) < 0.
On the other hand, based on the continuity t0> 0, it can be computed by evaluating the
model (4) along solutions at time t0,
{
b1e−d1τ1ϕ1(t0− τ1), 0 ≤ t0≤ τ1,
x˙1(t0) =
b1e−d1τ1 x1(t0− τ1), t0> τ1.
It follows from initial conditions (5) that x˙1(t0) > 0, which is a contradiction. Consequent
ly, x1(t) > 0 for all t > 0.
By using the similar arguments, it is easy to show that x2(t) > 0 for all t > 0.
Theorem 2. All solutions of model (4) with initial conditions (5) are ultimately bounded.
Proof.It follows from the ﬁrst equation of model (4) that
x˙1(t) ≤ b1e−d1τ1x1(t − τ1) − a11x1+1 θ1(t).
Considering the following auxiliary equation
z˙(t) = b1e−d1τ1z(t − τ1) − a11z1+θ1(t),
where z(t) = ϕ1(t) for t ∈ [−τ1, 0].
It is easy to show that z(t) ≥ x1(t) > 0 for all t > 0. Furthermore, it follows from Theorem
2 in [28] that z(t) is ultimately bounded, which implies there exists N1> 0 and T1> τ1
satisfying that x1(t) < N1for all t ≥ T1− τ1.
 6 
http://www.paper.edu.cn
By using the similar arguments, it is easy to show that there exists N2> 0 and T2> τ2
satisfying that x2(t) < N2for all t ≥ T2− τ2.
Consequently, all solutions of model (4) with initial conditions (5) are ultimately bounded.
According to model (4), nonnegative boundary equilibrium and interior equilibrium satis
ﬁes the following equation,
{
x1(b1e−d1τ1− a11xθ11 − a12x2− q1E1) = 0,
x2(b2e−d2τ2 − a22xθ22 − a21x1− q2E2) = 0.
For the sake of simplicity, some transformations are proposed,
(7)
f1= (
b1
a11
1
) θ1 , f2= (
b2
a22
1
) θ2 , c12=
a12f1
b1
q1
, c21=
q2
a21f2
b2
,
η1= d1τ1, η2= d2τ2, p1=
and then Eqn. (7) can be rewritten as follows:
{
b1
, p2=
b2
,
b1x1(e−η1 − (xf11)θ1 −c12f1x2 − p1E1) = 0,
b2x2(e−η2− (xf22)θ2−c21f2x1 − p2E2) = 0.
(8)
By solving Eqn. (8), three nonnegative boundary equilibria and a unique interior equilib
rium are as follows:
(i) M0(0, 0), which biologically implies that all competing species die out.
(ii) M1(˜1, 0), which biologically implies that x1species survives and x2species dies out. ˜1
takes the following form based on Eqn. (8),
˜1= f1(e−η1 − p1E1)1
θ1 , or ˜1=
f2(e−η2 − p2E2)
c21
,
which derives that M1(˜1, 0) exists provided that
e−η1
0 < E1< , or 0 < E2<
p1
e−η2
p2
.
(iii) M2(0, ˆ2), which biologically implies that x2species survives and x1species dies out. ˆ2
takes the following form based on Eqn. (8),
1
ˆ2= f2(e−η2− p2E2) θ2 , or ˆ2=
which derives that M2(0, ˆ2) exists provided that
e−η2
f1(e−η1− p1E1)
c12
e−η1
,
0 < E2<
p2
, or 0 < E1<
 7 
p1
.
(iv) A unique interior equilibrium M ∗(x∗1, x∗2) biologically implies that all competing species
survive and M ∗(x∗1, x∗2) exists provided that
or
{
{
1
f1c21(e−η1 − p1E1) θ1 > f2(e−η2 − p2E2),
1
f2c12(e−η2− p2E2) θ2> f1(e−η1− p1E1).
1
f1c21(e−η1− p1E1) θ1 < f2(e−η2− p2E2),
1
f2c12(e−η2 − p2E2) θ2 < f1(e−η1 − p1E1).
2 Local Stability Analysis
In this section, by analyzing associated characteristic equation, local stability of model (4)
around nonnegative boundary equilibrium and interior equilibrium is discussed, respectively.
Theorem 3. IfE1>p11andE2>p12hold, then model (4) is locally stable aroundM0.
Proof.It follows from model (4) that the characteristic equation evaluated around M0(0, 0) is
as follows,
(λ − b1e−(d1+λ)τ1+ q1E1)(λ − b2e−(d2+λ)τ2+ q2E2) = 0.
(11)
Let G1(λ) = λ and G2(λ) = b1e−(d1+λ)τ1 − q1E1, it easy to show that curve of G1(λ) and
G2(λ) must intersect at some negative value provided that E1>p11.
Similarly, let G3(λ) = b2e−(d2+λ)τ2 − q2E2, it easy to show that curve of G1(λ) and G3(λ)
must intersect at some negative value provided that E2>1
p2.
It follows from the above analysis that all eigenvalues of Eqn. (11) satisﬁes that Reλ1< 0
and Reλ2< 0. Hence, according to RouthHurwitz criteria [4], model (4) is locally stable
around M0provided that E1>p11and E2>p12.
Theorem 4. If 0 < E1<e−p1η1 −p11(ba2e21−fη12)θ1 holds, then model (4) is locally stable around
1
M1(˜1, 0)i.e. (f1(e−η1− p1E1) θ1 , 0).
Proof.It follows from model (4) that the characteristic equation evaluated around M1(˜1, 0) is
as follows,
(λ − b1e−(d1+λ)τ1+ a11˜θ11 (1 + θ1) + q1E1)(λ − b2e−(d2+λ)τ2+ a21˜1+ q2E2) = 0.
Let G4(λ) = λ − b1e−(d1+λ)τ1+ a11˜θ11 (1 + θ1) + q1E1. By substituting λ1= u1+ iv1into
G4(λ) = 0, where u1and v1are real number, it follows from Eqn. (7) that
G4(λ1) = u1+ iv1− b1e−(d1+u1)τ1e−iv1τ1+b1e−d1τ1+a11θ1˜θ11= 0.
According to (13), it can be obtained that ReG4(λ1) = 0.
In the following part, we will show that u1< 0. If u1≥ 0, then
ReG4(λ1) ≥ b1(1 − e−(d1+u1)τ1cos(v1τ1)) + θ1(b1e−d1τ1− q1E1) > 0,
which is a contradiction. Hence, it can be concluded that u1< 0.
Furthermore, consider the equation
λ − b2e−(d2+λ)τ2+ a21˜1+ q2E2= 0.
By substituting λ2= u2+ iv2into Eqn. (14), where u2and v2are real number, it follows
from Eqn. (7) that
u2+ a21˜1+ q2E2+ iv2 = b2e−η2 e−λ——2τ2 ,
If u2≥ 0, then we have,
(u2+ a21˜1+ q2E2)2+ v22 ≤ (b2e−η2)2,
and
a21˜1+ q2E2≤ b2e−η2.
It follows from the above analysis and Eqn. (8) that
−
E1≥
1 b
[e−η1 − (
2e
η1
)θ1],
p1
a21f1
which is a contradiction to the assumption of Theorem 4. Hence, it can be concluded that
u2< 0.
Based on the above analysis, all eigenvalues of Eqn.(12) satisﬁes that Reλ1< 0, Reλ2< 0.
It follows from RouthHurwitz criteria [4] that model (4) is locally stable around M1(f1(e−η1 −
1
−η
1
−
η2
p1E1) θ1 , 0) provided that 0 < E1<ep1−p11(b2e
θ
a21f1)1.
Theorem 5. If 0 < E2<e−p2η2 −p12(ba1e12−fη21)θ2 holds, then model (4) is locally stable around
1
M2(0, ˆ2)i.e. (0, f2(e−η2− p2E2) θ2 ).
Proof.It follows from model (4) that the characteristic equation evaluated around M2(0, ˆ2) is
as follows,
(λ − b1e−(d1+λ)τ1+ a12ˆ2+ q1E1)(λ − b2e−(d2+λ)τ2+ a22ˆθ22 (1 + θ2) + q2E2) = 0.
(15)
Let G5(λ) = λ − b2e−(d2+λ)τ2+ a22ˆθ22 (1 + θ2) + q2E2. By substituting λ3= u3+ iv3into
G5(λ) = 0, where u3and v3are real number, it follows from Eqn. (7) that
G5(λ3) = u3+ iv3− b2e−(d2+u2)τ2e−iv2τ2+b2e−d2τ2+a22θ2ˆθ22= 0.
According to (16), it can be obtained that ReG5(λ3) = 0.
 9 
(16)
In the following part, we will show that u3< 0. If u3≥ 0, then
ReG5(λ3) ≥ b2(1 − e−(d2+u3)τ2cos(v3τ2)) + θ2(b2e−d2τ2− q2E2) > 0,
which is a contradiction. Hence, it can be concluded that u3< 0.
Furthermore, consider the equation
λ − b1e−(d1+λ)τ1+ a12ˆ2+ q1E1= 0.
By substituting λ4= u4+ iv4into Eqn. (17), where u4and v4are real number, it follows
from Eqn. (7) that
u4+ a12ˆ2+ q1E1+ iv4 = b1e−η1 e−λ4τ1 ,
If u4≥ 0, then we have,
(u4+ a12ˆ2+ q1E1)2+ v42 ≤ (b1e−η1)2,
and
a12ˆ2+ q1E1≤ b1e−η1.
It follows from the above analysis and Eqn. (8) that
−
E2≥
1 b
[e−η2 − (
1e
η1
)θ2],
p2
a12f2
which is a contradiction to the assumption of Theorem 5. Hence, it can be concluded that
u4< 0.
Based on the above analysis, all eigenvalues of Eqn.(15) satisﬁes that Reλ3< 0, Reλ4< 0.
It follows from RouthHurwitz criteria [4] that model (4) is locally stable around M2(0, f2(e−η2 −
1
−η
2
−
η1
p2E2) θ2 ) provided that 0 < E2<ep2−p12(b1e
θ
a12f2)2.
It follows from Theorem 3 that both competing species x1and x2will face up with ex
tinction when harvest eﬀort E1and E2crosses critical valuep11andp12, respectively. If harvest
eﬀort E1is constrained within certain range (0,e−pη1
− 1
b
−
η2
p1(2e
θ
1
a21f1)1), extinction of species x1can
be avoided while interspeciﬁc competition has negative eﬀect on survival of competing species
x2, which can be found in Theorem 4.
Similarly, extinction of species x2can be avoided while interspeciﬁc competition has neg
ative eﬀect on survival of competing species x1provided that harvest eﬀort E2is constrained
within (0,e−η2
−
η1
p2 −p12(b1e
θ
a12f2)2), which can be found in Theorem 5.
Theorem 6. Model (4) is locally stable around the interior equilibriumM ∗(x∗1, x∗2)provided
that inequality (10) holds.
Proof.The characteristic equation of model (4) around the interior equilibrium M ∗(x∗1, x∗2) is
as follows:
[λ − b1e−(λ+d1)τ1+ a11(1 + θ1)x∗1θ1+a12x∗2+ q1E1]
×[λ − b2e−(λ+d2)τ2+ a22(1 + θ2)x∗2θ2+a21x∗1+ q2E2] − a12a21x∗1x∗2= 0.
(18)
By virtue of Eqn. (8), Eqn. (18) can be rewritten as follows,
[λ + b1e−η1(1 − e−λτ1) + a11θ1x∗1θ1][λ + b2e−η2(1 − e−λτ2) + a22θ2x∗2θ2]− a12a21x∗1x∗2= 0. (19)
Let λ5= u5+ iv5be an arbitrary solution of Eqn. (19), where u5and v5are real number.
By substituting λ5= u5+ iv5into Eqn. (19), it gives that,
(A1+ iB1)(A2+ iB2) − a12a21x∗1x∗2= 0,
where Akand Bk(k = 1, 2) are deﬁned as follows:
A1= u5− b1e−(d1+u5)τ1cos(v5τ1) + a11(1 + θ1)x∗1θ1+ a12x∗2+ q1E1,
B1= v5+ b1e−(d1+u5)τ1sin(v5τ1),
A2= u5− b2e−(d2+u5)τ2 cos(v5τ2) + a22(1 + θ2)x∗2θ2+ a21x∗1+ q2E2,
B1= v5+ b2e−(d2+u5)τ2sin(v5τ2).
Further computations show that
A1A2− B1B2= a12a21x∗1x∗2, A1B2+ A2B1= 0,
which derives that
A1A2≤ a12a21x∗1x∗2.
We claim that u5< 0. On the contrary, based on Eqn. (8), it is easy to show that
A1≥ a11θ1x∗1θ1+b1e−η1 − b1e−η1−u5τ1 cos(v5τ1)
≥ a11θ1x∗1θ1+b1e−η1− b1e−η1> 0,
and
A2≥ a22θ2x∗2θ2+b2e−η2− b2e−η2−u5τ2cos(v5τ2)
≥ a22θ2x∗2θ2+b2e−η2− b2e−η2> 0.
Hence, we have
A1A2≥ a11a22θ1θ2x∗1θ1x∗2θ2.
Based on (22) and (23), it can be derived that
a12a21(x∗1)1−θ1(x∗2)1−θ2≥ a11a22θ1θ2.
On the other hand, denote Li, i = 1, 2 as the curve about x1and x2in R2+, respectively.
{
−d
L1: x2=b1e
−
1τ1−q1E1
a12
− 
a11 a12xθ11, 
L2: x1=b2ed2aτ212−q2E2−aa2221xθ22.
By simple computation, the slope kLi of curve Li, i = 1, 2 can be obtained as follows:
kL1=dx2L1=−a11
θ1(x1)θ1−1,kL2=
dx2
L2=−
1
.
dx1
dx1
a22
θ
a12
a21θ2(x2)2−1
If inequality (10) holds, then it is easy to show that kL1< kL2< 0 around the interior
equilibrium M ∗(x∗1, x∗2), which derives that
a11a22θ1θ2(x∗1)θ1−1(x∗2)θ2−1> a12a21,
which contradicts to (24). Consequently, it can be concluded that u5< 0.
Since λ5= u5+ iv5is an arbitrary solution of Eqn. (19) and Reλ5< 0, it follows from
RouthHurwitz criteria [4] that model (4) is locally stable around M ∗(x∗1, x∗2) provided that
inequality (10) holds.
It is easy to show that model (4) is locally unstable around the nonnegative boundary
equilibrium M1(˜1, 0) and M2(0, ˆ2) provided that inequality (10) holds. Consequently, local
stability around M1(˜1, 0) and M2(0, ˆ2) can not be preserved while the interior equilibrium
M ∗ is locally stable.
3 Global Stability Analysis
In this section, global stability of the nonnegative boundary equilibrium M1and M2is
investigated based on an iterative technique, respectively. By constructing an appropriate
Lyapunov functional, global stability of the unique interior equilibrium is also discussed.
Lemma 1. [27] Considering the following diﬀerential equation,
z˙(t) = αz(t − τ1) − βz1+θ(t) − γz(t).
Ifα > γ ≥ 0, thenlimt→∞ z(t) = ( α−β γ)1θ.
Theorem 7. If the following equalities hold
0 < E1<
e−η1
p1
−1(
p1
b2e−η2
a21f1
)θ1, 0 < E2<
e−η2
p2
−1(
p2
b1e−η1
a12f2
)θ2,
(26)
thenM1(˜1, 0) is globally asymptotically stable, wherefi, ηi, pi,i = 1, 2have been deﬁned in
(8).
 12 
Proof. According to (26), it follows from Theorem 4 that model (4) is locally stable around
M1, and the global stability of M1will be proved in the following part.
Let
I1= lim inf x1(t), J1= lim sup x1(t),
t→∞
t→∞
I2= lim inf x2(t), J2= lim sup x2(t).
t→∞
t→∞
It follows from Theorem 1 and the ﬁrst equation of model (4) that
x˙1(t) ≤ b1e−d1τ1x1(t − τ1) − a11x1+1 θ1(t) − q1E1x1(t).
By virtue of (26), it is easy to show that b1e−d1τ1 > q1E1, and it follows from Lemma 4.1
that there exists T1> 0 and when t > T1,
−
b1ed1τ1− q1E11
x1(t) ≤ (
holds for suﬃciently small ϵ > 0.
a11
) θ1 + ϵ := V1x1
(27)
It follows from Theorem 1 and the second equation of model (4) that
x˙2(t) ≤ b2e−d2τ2x2(t − τ2) − a22x1+2 θ2(t) − q2E2x2(t).
By virtue of (26), it is easy to show that b2e−d2τ2 > q2E2, and it follows from Lemma 4.1
that there exists T2> T1and when t > T2,
−
b2ed2τ2− q2E21
x2(t) ≤ (
holds for suﬃciently small ϵ > 0.
a22
) θ2+ ϵ := V1x2
(28)
Based on (28) and the ﬁrst equation of model (4), it can be obtained that
x˙1(t) ≥ b1e−d1τ1x1(t − τ1) − a11x1+1 θ1(t) − (a12V1x2+q1E1)x1(t).
By virtue of (26), it is easy to show that b1e−d1τ1 > a12V1x2+ q1E1, and it follows from
Lemma 4.1 that there exists T3> T2and when t > T3,
−
b1ed1τ1− a12V1x2 − q1E11
x1(t) ≥ (
holds for suﬃciently small ϵ > 0.
a11
) θ1− ϵ := U1x1
(29)
Based on (27) and the second equation of model (4), it can be obtained that
x˙2(t) ≥ b2e−d2τ2x2(t − τ2) − a22x1+2 θ2(t) − (a21V1x1+q2E2)x2(t).
By virtue of (26), it is easy to show that b2e−d2τ2 > a21V1x1+ q2E2, and it follows from
Lemma 4.1 that there exists T4> T3and when t > T4,
−
b2ed2τ2 − a21V1x1 − q2E21
x2(t) ≥ (
a22
 13 
) θ2− ϵ := U1x2
(30)
holds for suﬃciently small ϵ > 0.
According to (30) and the ﬁrst equation of model (4), it derives that
x˙1(t) ≤ b1e−d1τ1x1(t − τ1) − a11x1+1 θ1(t) − (a12U1x2+ q1E1)x1(t).
By virtue of (26), it is easy to show that b1e−d1τ1 > a12U1x2+q1E1, and it follows from
Lemma 4.1 that there exists T5> T4and when t > T5,
−
b1ed1τ1 − a12U1x2 − q1E11
x1(t) ≤ (
holds for suﬃciently small ϵ > 0.
a11
) θ1 + ϵ := V2x1
(31)
It follows from (29) and the second equation of model (4) that
x˙2(t) ≤ b2e−d2τ2x2(t − τ2) − a22x1+2 θ2(t) − (a21U1x1+ q2E2)x2(t).
By virtue of (26), it is easy to show that b2e−d2τ2 > a21U1x1+q2E2, and it follows from
Lemma 4.1 that there exists T6> T5and when t > T6,
−
b2ed2τ2 − a21U1x1− q2E21
x2(t) ≤ (
holds for suﬃciently small ϵ > 0.
a22
) θ2 + ϵ := V2x2
(32)
Based on (32) and the ﬁrst equation of model (4), it can be obtained that
x˙1(t) ≥ b1e−d1τ1x1(t − τ1) − a11x1+1 θ1(t) − (a12V2x2+ q1E1)x1(t).
By virtue of (26), it is easy to show that b1e−d1τ1 > a12V2x2+q1E1, and it follows from
Lemma 4.1 that there exists T7> T6and when t > T7,
−
b1ed1τ1 − a12V1x2− q1E11
x1(t) ≥ (
holds for suﬃciently small ϵ > 0.
a11
) θ1 − ϵ := U2x1
(33)
Based on (31) and the second equation of model (4), it can be obtained that
x˙2(t) ≥ b2e−d2τ2 x2(t − τ2) − a22x1+2 θ2(t) − (a21V2x1+ q2E2)x2(t).
By virtue of (26), it is easy to show that b2e−d2τ2 > a21V2x1+ q2E2, and it follows from
Lemma 4.1 that there exists T8> T7and when t > T8,
−
b2ed2τ2 − a21V2x1− q2E21
x2(t) ≥ (
holds for suﬃciently small ϵ > 0.
a22
) θ2 − ϵ := U2x2
(34)
Continuing the above processes, it follows from (27)(34) that four sequences {Vnx1}, {Vnx2},
{Unx1} and {Unx2 }, n = 1, 2, · · · can be obtained, which take the following form for n ≥ 2:
−d1τ1 −a12Unx−21−q1E1
Vnx1 = (b1e
−
a11
1
) θ1+ ϵ,
Vnx2= (b2ed2τ2 −a21Unx−11−q2E2
1
) θ2 + ϵ,
−d
a22
(35)
Unx1= (b1e
1τ1−a12Vnx2−q1E1
a11
1
) θ1 − ϵ,
−d
Unx2 = (b2e
2τ2−a21Vnx1−q2E2
a22
 14 
1
) θ2 − ϵ.
By virtue of (35), it can be derived that
b
−d1τ1− a12Vnx−21 − q1E1
a22(Vnx2)θ2=b2e−d2τ2 − q2E2− a21(1e
which follows that
a11
1
) θ1 ,
(36)
(
b2e−d2τ2 − q2E2− a22(Vnx2 )θ2
a21
)θ1 =
b1e−d1τ1− a12Vnx−21 − q1E1
a11
.
(37)
Since Vnx2≥ I2and {Vnx2} is monotonically decreasing based on mathematical induction,
it can be obtained that limn→∞ Vnx2 = h ≥ 0 exists.
By limiting (37) with n → ∞, it gives that
(C1− C2hθ2)θ1= C3− C4h,
where C1=b2e−d2aτ212−q2E2, C2=aa2221,C3=b1e−d1aτ111−q1E1, C4=aa1211.
According to (26) and (38), it can be computed that
−
b2ed2τ2− q2E2
(38)
C1− C2hθ2> C1− C2
a22
= 0,
which derives that C3− C4h > 0 and 0 ≤ h < h2where h2=b1e−d1aτ1−q1E1.
12
In order to show this theorem, we only need to discuss that h = 0 and the following two
cases will be considered.
Case I.θ1≥ 1, θ2≥ 1.
Firstly, denote Lk, k = 3, 4 as the curve about yj, j = 1, 2 and h in R2+, respectively.
{
L3: y1(h) = (C1− C2hθ2 )θ1,
L4: y2(h) = C3− C4h.
By simple computation, it derives that
dddy2hy11= −θ1θ2C2hθ2−−1(C1− C2hθ2)θ1−1<0,
dh2=−θ1θ2C2hθ22(C1− C2hθ2)θ1−2[(θ2− 1)(C1− C2hθ2) − (θ1− 1)θ2C2hθ2],
dy2
dh=−C4< 0,
d2y2
(39)
(40)
dh2= 0.
It follows from (40) that
d2y1
dh2=
<0, 0 ≤ h < h1,
0, h = h1,
>0, h1< h ≤ h2.
 15 
(41)
where h1=
C1(θ2−1)
C2[(θ2−1)+θ2(θ1−1)].
Let y(h) = y1(h) − y2(h), y1(h) and y2(h) have been deﬁned in (39). Next, four steps are
provided to show that limt→∞ x2(t) = 0.
(i) there is at most one intersection forL3andL4whenh ∈ [0, h1].
If this claim is false, then there are at least two intersection, h11and h12s.t., y(h11) = 0
and y(h12) = 0. It follows from (41) that y′′(h) < 0 when h ∈ [0, h1], which derives that
y′(h) is monotonically decreasing. Furthermore, we claim that y′(h11) ≤ 0. Otherwise, if
y′(h11) > 0, then y′(h) > 0 when h ∈ [0, h11]. It follows from y(h11) = 0 that y(0) < 0.
According to deﬁnition of y(h) and Eqn. (7), it can be obtained that y(0) = 0, which is
a contradiction.
By using similar arguments, we have y′(h12) ≤ 0, which follows that y′(h) < 0 when
h ∈ (h11, h12). On the other hand, there exists ξ1∈ (h11, h12) s.t. y′ (ξ1) = 0 based on
y(h12) = y(h12) = 0, which is a contradiction.
Hence, L3and L4have at most one intersection when h ∈ [0, h1].
(ii) there is at most one intersection for L3and L4when h ∈ [h1, h2].By using the
similar arguments in step (i), it can be shown that L3and L4have at most one intersection
when h ∈ [h1, h2].
(iii) there is no intersection forL3andL4whenh ∈ [h1, h2].
Suppose there is one intersection h21∈ (h1, h2) for L3and L4. Based on the arguments
in step (i) and (ii), we have y′(h21) ≤ 0. It follows from y′(h11) ≤ 0 and y′(h21) ≤ 0
that y′(h) ≤ 0 when h ∈ (h11, h21). On the other hand, there exists ξ2∈ (h11, h21) s.t.,
y′(ξ2) = 0, which is a contradiction.
Consequently, there is no intersection for L3and L4when h ∈ [h1, h2].
(iv) there is no intersection forL3andL4whenh ∈ (0, h1).
Otherwise, if there is one intersection h0∈ (0, h1). Since there exists no intersection for
L3and L4when h ∈ [h1, h2]. It is easy to see that h0∈ (0, h2) and the solution of Eqn.
(38) is either 0 or h0> 0.
In the following part, we will show that h̸= h0. According to the arguments for ﬁnding
sequences Unx1 and Vnx2 utilized in the above steps, we can ﬁnd two new sequences U˜nx1
and ˜nx2, such that x1≥ U˜nx1and x2≤ V˜nx2, where
{
b
−d2τ2 −a21U˜nx−11−q2E2
1
˜ x2
n= (
2e
a22
) θ2 + ϵ,
(42)
U˜nx1= (b1e−d1τ1−aa12V˜nx2−q1E1
1
) θ1 − ϵ.
11
 16 
By virtue of (42), it can be concluded that
(C1− C2( ˜nx2)θ2)θ1= C3− C4V˜nx−21,
where Ci(i = 1, 2, 3, 4) have been deﬁned in (38).
(43)
Similarly, it is also easy to show that limn→∞ ˜nx2= ˜h ≥ 0 exists, which follows that
(C1− C2˜θ2)θ1= C3− C4˜h.
(44)
By using the similar arguments in step (i)(iv), we can also conclude that ˜ = 0 or ˜ = h0.
Since ˜nx2is monotonically decreasing, V˜nx2< V˜1x2=h0hold for all n ≥ 2. It follows from
the above analysis that ˜h < h0. Consequently, it can be concluded that ˜= 0.
Based on step (i)(iv), there must be h = 0, i.e. limt→∞ x2(t) = 0. It follows from (38) that
limn→∞ Unx1 = f1(e−η1 − p1E1) θ11 = ˜x1. Since Unx1 ≤ I1≤ J1≤ ˜1. Hence, limt→∞ x1(t) = ˜x1.
Case II.θ1< 1, θ2< 1.
By using similar proof with Case I, it is easy to show limt→∞ x1(t) = ˜x1and limt→∞ x2(t) =
0.
This completes the proof of Theorem 7.
By using the similar proof, global stability analysis of the boundary equilibrium M2(0, ˆ2)
can be concluded as follows.
Theorem 8. If the following equalities hold
0 < E1<
e−η1
p1
−1(
p1
b2e−η2
a21f1
)θ1, 0 < E2<
e−η2
p2
−1(
p2
b1e−η1
a12f2
)θ2,
(45)
thenM2(0, ˆ2) is globally asymptotically stable, wherefi, ηi, pi,i = 1, 2have been deﬁned in
(8).
Theorem 9. Interior equilibrium M ∗(x∗1, x∗2) is globally stable provided that inequality (10)
holds.
Proof. Firstly, let N(z) = z − ln z − 1 for all z > 0. By simple computation, it can be obtained
that N(z) ≥ 0 for all z ≥ 0 and N(z) = 0 if and only if z = 1. Nextly, we deﬁne the Lyapunov
functional
W (t) = W1(t) + W2(t),
where W1(t) and W2(t) are deﬁned as follows:
∗
W1(t) = x∗1N (xx1(∗t)) +a12x
2
x2(t)
),
a21N (x∗
1
∫
0
2
−d
∫0
W2(t) = b1e−d1τ1x∗1
x1(t+ζ))dζ +a12b2e
2τ2x∗
x2(t+ζ)
−τ1N(
x∗
a21
2
−τ2N(
x∗
)dζ.
1
2
According to deﬁnition of W (t), it is easy to show that W (t) ≥ 0 for all t ≥ 0.
 17 
that
By calculating the derivative of W1(t) and W2(t) along the solution of model (4), it gives
W˙1(t) = x∗1(1−1
)[b1e−d1τ1x1(t − τ1) − a11x(1+1 θ1)(t) − a12x1(t)x2(t) − q1E1x1(t)]
+
x 
∗ 1 
a12x∗2
a21
∗
(
x1(t)
1 −1
x∗2x2(t)
)[b2e−d2τ2x2(t − τ2) − a22x(1+2 θ2)(t)]
and
−a12x
2
a21
(
1 −1
x∗2x2(t)
∗
)[a21x1(t)x2(t) + q2E2x2(t)],
W˙2(t) = (1 −x1
x1(t)
)[b1e−d1τ1 x1(t) − a11x(1+1 θ1)(t) − a12x1(t)x2(t) − q1E1x1(t)]
x∗
+b1e−d1τ1(1 −
1
x1(t)
)[x1(t − τ1) − x1(t)]
x
+b1e−d1τ1[x1(t) − x1(t − τ1) + x∗1ln(
1(t − τ1)
x1(t)
)]
+
a12
a21
(1 −
x∗
2
x2(t)
)[b2e−d2τ2x2(t) − a22x(1+2 θ2)(t) − a21x1(t)x2(t) − q2E2x2(t)]
+
a12b2e−d2τ2
a21
a12b2e−d2τ2
(1 −
x∗
2
x2(t)
)(x2(t − τ2) − x2(t))
x
+
a21
[x2(t) − x2(t − τ2) + x∗2ln(
2(t − τ2)
x2(t)
)]
= (x1(t) − x∗1)[b1e−d1τ1− a11xθ11(t) − a12x2(t) − q1E1]
a12
+
a21
(x2(t) − x∗2)[b2e−d2τ2− a22xθ22 (t) − a21x1(t) − q2E2]
−b1e−d1τ1x∗1[x1(t − τ1) − lnx1(t − τ1) − 1]
x1(t) x1(t)
−d2τ2x∗2x2(t − τ2)
−a12b2e
a21
[
x2(t)
− lnx2(t − τ2) − 1].
x2(t)
 18 
Hence, it can be obtained that
W˙ (t) = (x1(t) − x∗1)[a11(x∗1)θ1+a12x∗2− a11xθ11(t) − a12x2(t)]
a12
+
a21
(x2(t) − x∗2)[a22(x∗2)θ2+ a21x∗1− a22xθ22(t) − a21x1(t)]
−
−b1e−d1τ1x∗1N (x1(t − τ1)
) −
a12b2ed2τ2x∗2
N(
x2(t − τ2)
)
x1(t)
= a11(x1(t) − x∗1)[(x∗1)θ1 − xθ11(t)] +
a21
a
12a22
a21
−
x2(t)
(x2(t) − x∗2)[(x∗2)θ2 − xθ22(t)]
−b1e−d1τ1x∗1N (x1(t − τ1)
) −
a12b2ed2τ2x∗2
N(
x2(t − τ2)
)
a12a21
x1(t)
a21
x2(t)
+(a12−
a21
)(x1(t) − x∗1)(x2(t) − x∗2)
a
= a11(x1(t) − x∗1)[(x∗1)θ1− xθ11(t)] +
12a22
a21
(x2(t) − x∗2)[(x∗2)θ2− xθ22 (t)]
−b1e−d1τ1x∗1N (x1(t − τ1)
) −
−d2τ2x∗2
a12b2e
N(
x2(t − τ2)
).
x1(t)
a21
x2(t)
By straightforward computation, it is easy to show that
x
for i = 1, 2.
[xi(t) − x∗i][(x∗i)θi− xθii(t)] ≤ 0, N (
i(t − τi)
xi(t)
) ≥ 0,
Consequently, it can be concluded that W˙ (t) ≤ 0, which follows that W (t) is bounded,
nonincreasing and limt→∞ W (t) exists.
By using the similar arguments in Theorem 2 in [29], it is easy to show that
lim x1(t) = x∗1, lim x2(t) = x∗2.
t→∞
4 Numerical Simulation
t→∞
Numerical simulations are carried out to show consistency with the global stability analysis
discussed in the case of θ1≥ 1, θ2≥ 1 and θ1< 1, θ2< 1.
Numerical Simulation I.Parameter values are partially taken from [27] and [4], which are
given as follows: b1= 2, d1= 0.5, τ1= 2.8, a11= 1.5, a12= 1, q1= 1, E1= 0.2, b2= 2.5,
d2= 0.6, τ2= 3, a22= 1.5, a21= 1, q2= 1, E2= 0.1. By simple computation, it can be
−η
−η
obtained that 0 < E1<e−η1 − 1 ( b2e
2)θ1and 0 < E2<e−η2 − 1 ( b1e
1)θ2with θ1= 2
p1
p1
a21f1
p2
p2
a12f2
and θ2= 1.9. It follows from Theorem 7 that M1(0.4422, 0) is globally stable, and dynamical
responses of model (4) with θ1= 2 and θ2= 1.9 are plotted in Figure 1. Furthermore, it
can be computed that 0 < E1<e−pη1
− 1
b
−
η2
−η2
−
η1
p1(2e
θ
a21f1)1and 0 < E2<ep2−p12(b1e
θ
1
a12f2)2with
θ1= 0.45 and θ2= 0.1263. It follows from Theorem 7 that M1(0.0265, 0) is globally stable,
and dynamical responses of model (4) with θ1= 0.45 and θ2= 0.1263 are plotted in Figure 2.
 19 
0.7
0.6
0.5
0.4
0
0.2
0.1
0
−0.1
0
200
200
400
400
Time
600
600
800
800
1000
1000
图 1: Dynamical responses of the nonnegative boundary equilibrium M1(0.4422, 0) of model
(4) with θ1= 2 and θ2= 1.9, which indicates that M1(0.4422, 0) is globally stable.
Numerical Simulation II.Parameter values are partially taken from [27] and [4], which
are given as follows: b1= 2, d1= 0.5, τ1= 3, a11= 1.5, a12= 1, q1= 1, E1= 0.15, b2= 2.5,
d2= 0.6, τ2= 1, a22= 1.5, a21= 1, q2= 1, E2= 0.08. By simple computation, it can be
obtained that 0 < E1<e−pη11 −p11(ba221e−fη12)θ1 and 0 < E2<e−pη22 −p12(ba112e−fη21)θ2 with θ1= 2
and θ2= 1.9. It follows from Theorem 8 that M1(0, 0.9243) is globally stable, and dynamical
responses of model (4) with θ1= 2 and θ2= 1.9 are plotted in Figure 3. Furthermore, it can be
computed that 0 < E1<e−pη1
− 1
b
−η2
θ
−η
2
−
η1
p1(2e
a21f1)1and 0 < E2<ep2−p12(b1e
θ
1
a12f2)2with θ1= 0.5 and
θ2= 0.5263. It follows from Theorem 8 that M1(0, 0.7531) is globally stable, and dynamical
responses of model (4) with θ1= 0.453 and θ2= 0.5263 are plotted in Figure 4.
 20 
0.4
0.3
0.2
0.1
0
0
0.8
0.6
0.4
0.2
0
0
200
200
400
400
Time
600
600
800
800
1000
1000
图 2: Dynamical responses of the nonnegative boundary equilibrium M1(0.0265, 0) of model
(4) with θ1= 0.45 and θ2= 0.1263, which indicates that M1(0.0265, 0) is globally stable.
0.2
0.1
0
−0.1
0
1
0.8
0.6
0.4
0.2
0
200
200
400
400
Time
600
600
800
800
1000
1000
图 3: Dynamical responses of the nonnegative boundary equilibrium M2(0, 0.9243) of model
(4) with θ1= 2 and θ2= 1.9, which indicates that M2(0, 0.9243) is globally stable.
 21 
0.2
0.1
0
−0.1
0
0.8
0.7
0.6
0.5
0.4
0
200
200
400
400
Time
600
600
800
800
1000
1000
图 4: Dynamical responses of the nonnegative boundary equilibrium M2(0, 0.7531) of model
(4) with θ1= 0.5 and θ2= 0.5263, which indicates that M2(0, 0.7531) is globally stable.
Numerical Simulation III.Parameter values are partially taken from [27] and [4], which
are given as follows: b1= 2, d1= 0.5, τ1= 0.75, a11= 1.5, a12= 1, q1= 1, E1= 0.1, b2= 2.5,
d2= 0.6, τ2= 0.95, a22= 1.5, a21= 1, q2= 1, E2= 0.05. By simple computation, it can be
obtained that
1
1
f1c21(e−η1 − p1E1) θ1< f2(e−η2 − p2E2), f2c12(e−η2 − p2E2) θ2< f1(e−η1 − p1E1)
with θ1= 2 and θ2= 1.9, which implies that inequality (10) holds. It follows from Theorem 9
that M ∗(0.6247, 0.6885) is globally stable, and dynamical responses of model (4) with θ1= 2
and θ2= 1.9 are plotted in Figure 5.
Furthermore, it can be computed that
1
1
f1c21(e−η1− p1E1) θ1 < f2(e−η2− p2E2), f2c12(e−η2− p2E2) θ2 < f1(e−η1− p1E1)
with θ1= 0.23 and θ2= 0.14, which implies that inequality (10) holds. It follows from
Theorem 9 that M ∗(0.4433, 0.0308) is globally stable, and dynamical responses of model (4)
with θ1= 0.23 and θ2= 0.14 are plotted in Figure 6.
5 Conclusion
In this paper, the combined dynamic eﬀect of maturation delay and harvest eﬀort on
twospecies competition ecosystem is investigated. Generally, positivity and boundedness of
 22 
0.65
0.6
0.55
0
0.8
0.7
0.6
0.5
0.4
0
200
200
400
400
Time
600
600
800
800
1000
1000
图 5: Dynamical responses of the unique interior equilibrium M ∗(0.6247, 0.6885) of model (4)
with θ1= 2 and θ2= 1.9, which indicates that M ∗(0.6247, 0.6885) is globally stable.
0.5
0.4
0.3
0
0.25
0.2
0.15
0.1
0.05
0
0
200
200
400
400
Time
600
600
800
800
1000
1000
图 6: Dynamical responses of the unique interior equilibrium M ∗(0.4433, 0.0308) of model (4)
with θ1= 0.23 and θ2= 0.14, which indicates that M ∗(0.4433, 0.0308) is globally stable.
 23 
solution biologically interpret sustainable survival of two competing species, which is studied in
Theorem 1 and Theorem 2, respectively. Some suﬃcient conditions are provided to show the
existence of three nonnegative boundary equilibria and a unique interior equilibrium. Further
attempts are carried out to discuss local stability analysis around nonnegative boundary equi
librium and interior equilibrium. It reveals that two competing species will come to extinction
when harvest eﬀort crosses certain critical value, respectively. It is shown that increase of
the maturation delay of one species has negative eﬀect on its permanence and a suﬃciently
large maturation delay will directly lead to its extinction. Further discussions show that har
vest eﬀort on one species may change the surviving or extinction behavior of the harvested
species and its competitor. If harvest eﬀort on competing species is constrained within certain
range, extinction of the corresponding species can be avoided while interspeciﬁc competition
has negative eﬀect on survival of its competing species. It should be noted that local stability
of boundary equilibrium can not be preserved while interior equilibrium is locally stable, which
can be found in Theorem 6. By using an iterative technique, global stability of the nonneg
ative boundary equilibrium is investigated in the case of θ1≥ 1, θ2≥ 1 and θ1< 1, θ2< 1,
respectively. Global stability of the unique interior equilibrium is also discussed by the means
of constructing an appropriate Lyapunov functional, which shows that two competing species
coexist and sustainable development of competing population ecosystem can be achieved when
maturation delay and harvest eﬀort are constrained within certain range.
Since many species within competition ecosystem are of agricultural and medical utiliza
tion, they are mostly harvested and sold with the purpose of obtaining the economic interest
[4]. Although there are much progress on GilpinAyala competition model, such model are
discussed in the sense that previously related work ignore commercial harvesting, which can
not vividly reﬂect complex biological phenomena from harvested competition ecosystem. Since
harvesting has a strong impact on the dynamic evolution of a population, it is necessary to
investigate the dynamic eﬀect of harvesting on population dynamics. Based on above analysis,
work done in [27] is extended by incorporating harvest eﬀort on two competing species, and
combined dynamic eﬀect of harvest eﬀort and maturation delays on population dynamics are
discussed. It should be noted that global stability analysis of nonnegative boundary and interior
equilibrium are relevant to investigation of coexistence and interaction mechanism of compet
ing species. These theoretical ﬁndings are of inspiration for administrative agency to regulate
commercial harvesting within appropriate limitations, especially for species with relatively long
maturation. It makes work done in this paper has some positive and new feature.
 24 
Acknowledgement
This work is supported by National Natural Science Foundation of China, grant No.
61104003, grant No. 61273008 and grant No. 61104093. Research Foundation for Doctor
al Program of Higher Education of Education Ministry, grant No. 20110042120016. Hebei
Province Natural Science Foundation, grant No. F2011501023. Fundamental Research Fund
s for the Central Universities, grant No. N120423009. Research Foundation for Science and
Technology Pillar Program of Northeastern University at Qinhuangdao, grant No. XNK201301.
This work is supported by State Key Laboratory of Integrated Automation of Process
Industry, Northeastern University, supported by Hong Kong Admission Scheme for Mainland
Talents and Professionals, Hong Kong Special Administrative Region.
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Describe a Challenging Situation  Client Admitted to Wharton Business School
The car engine started roaring breaking the tranquility of the quiet suburb. The beams of the headlight pierced through the evening darkness. The Honda Civic picked up speed from zero to 60 miles per hour within few seconds. As I drove in the expressway, I occasionally starred at the star filled night sky and thought “Is this my destiny?” I raced the car full speed on the interstate highway. But the events of the godforsaken day kept rolling in my mind.
Months back, I was asked to join our Regional Head Quarter at London. I was elated to receive such a big promotion. With superior monetary benefits and enhanced job responsibilities, I was enjoying my time in London with my colleagues and friends. Unaware of the gathering storm at our New York Global Headquarter, I even booked tickets for my first big music concert of Metallica on 15th September 2008 and could barely wait for the day to come.
On 15th Sep, 2008, I reached office with a cheerful mood. The hustle and bustle in the corridor was bigger than usual. I sensed uneasiness in the ambience. “What happened?” I asked someone at the entrance. He looked at me with a blank face and asked “You don’t know? Lehman has filed for bankruptcy”. The news came as a jolt. We all were mindful of the worsening financial crisis, but nobody really expected an investment bank as big as Lehman Brothers to fail. I entered the office building and saw complete mayhem. With now no job in picture for anybody, people were panicking about prior financial commitments and responsibilities. Some were packing their belongings while many were calling friends and head hunters for job openings. My entire planned career, which looked in the best shape less than a year ago, seemed to turn upside down. On the giant screen on the wall, I saw news reporter screaming with their breaking news on CNN about the largest bankruptcy filing the corporate history. At the desk, I sat alongside my boss watching him drafting his resume. Amidst the ongoing chaos, I kept my nerve, but things were to become worse. In the evening, I came back home. I thought that there was no better way to cheer myself up on that godforsaken day than with the Metallica concert! But within minutes, I got a call from the society office. I was asked to vacate the company apartment as the agency wasn’t sure whom to bill afterwards. I got almost choked. Without altering a single word, I packed my stuffs and left. From losing a dream job to being homeless, all in a span of few hours, I experienced the roller coaster ride of my life.
I stopped the car in the parking and checked in Hotel Plaza Inn. I took a shower. I was feeling refreshed. At the end of the day, I thought the best thing to do was just to stand quietly in the hotel balcony and enjoy the breeze. I looked at the London skyline and reminded myself that every cloud has a silver lining. I decided to stay back in London for some more time to face my destiny.
Instead of flying back to India or brooding about the situation, I continued going to office every day to network with senior associates. I realized the importance of a backup plan even when everything sails smooth as life is full of chance events. During the extra hours every day, which suddenly fell in my lap with no job, I explored around the city of London and knocked at every door for a suitable opening. It was the journey from a reckless, imprudent undergraduate with a trading job to a cautiously optimistic professional in a short span. I have continued to adapt myself to the changing world around and make the best out of every situation.
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Background
I raised this question because of an argument I am having with a question from user697473 here. The title of his question is "Formal definiton of random assignment." In the post he makes a claim that one can get unbiased estimates of the difference of treatment effect even if one group that is represented in the population is not sampled. At least that is the way I interpret the claim. He points to a paper coauthored by Don Rubin on causal modeling here. Both he and StasK argue through examples that this claim is true. This issue was also raised in another question that he posted here. In that post titled "Random assignment: why bother?" gung expresses skeptism.
In the first question my answer included a statement to the effect that without sampling all possible assignments of a potential confounding factor you cannot construct an estimate of the difference in treatment effect without assigning samples to each stratum for the confounding factor.
The Issue
I am confused about the claim. As I interpret the claim I am sure it is false. The claim is supported by two examples one given by user697473 and the other by StasK. The examples are confusing to me and in neither case is a proof or demonstration given to show that the claim is true.
I could be misinterpreting the claim but based on my interpetation it is false. To illustrate my point let's look at a famous example from the design of experiments book of the Godfather of randomization Sir Ronald Aylmer Fisher: "The Lady Tasting Tea".
In case you don't know the example I will describe it and provide a modification to clarify the example. The lady claims that she has the ability to determine just by tasting a cup of tea whether the tea was poured first or the milk was poured first. Fisher poses an experiment to test her claim by providing some cups with tea poured first and others with the milk poured first. If the Lady has the expertise that she claims she should be able to correctly identify the types better than a person who guesses at random. So the experiment is design to see if her probability of correct classification is better than 0.5. So he randomly provides the Lady with cups from both groups (in the example there were 6 cups 3 with milk poured first and 3 with tea poured first.
Now let me modify the experiment slightly. Suppose I have three brands of tea and for my population these brands are served at a tea parties equally. The question I want to ask is when given a cup of tea at a tea party can the Lady predict whether milk was poured first or the tea was poured first. I want to test whether her prediction accuracy is greater than 0.5 in the setting of tea parties. So I will apply Fisher's experiment to estimate this probability when the Lady is at one of these tea parties.
Note: I do not care whether or not she can differentiate the brands.
Suppose that in the population of tea parties the Lady's ability is:
Brand A Can predict tea first with probability 0.7 and can predict milk first with probability 0.7.
Brand B Can predict tea first with probability 0.75 and can predict milk first with probability 0.75.
Brand C Can predict tea first with probability 0.5 and can predict milk first with probability 0.6.
So she does no better than chance with Brand C but can do better than chance with Brands A and B.
For the experiment I only provide Brands A and B for her to taste. All I want to know is her ability to predict correctly in the normal tea party situation.
My Questions
Can I get an unbiased estimates of her prediction capabilities with this experiment?
If the answer to (1) is no, is user697473's claim false or have I misinterpreted it?
Randomization is used to avoid bias that is produced by confounding variables. This is important when trying to draw inference from a sample to a population. In my example the Brands are confounders. The treatment is tasting the cups. In the population she would get Brand A, Brand B and Brand C each 1/3rd of the time. If I know this and I sample Brands with unequal probabilities I claim that I can get an unbiased estimate of her prediction capabilities by taking a specific weighted average of the estimates of the proportions if I use a stratified random sample with strata totals n1, n2 and n3all greater than 0. But I cannot if n3 = 0. Furthermore, there is not other estimate I can calculate from a sample where allocation to Brand C equal 0 that will be an unbiased estimate.