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Populations and Community Ecology. Chapter 19 and Chapter 20. Population. - group of organisms that belong to the same species and live in a particular place at the same time. Population Density. - measures how crowded a population is; the number of individuals per unit of area or volume.
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Populations and Community Ecology Chapter 19 and Chapter 20
Population - group of organisms that belong to the same species and live in a particular place at the same time Population Density - measures how crowded a population is; the number of individuals per unit of area or volume When counting the plants in a forest, measure and rope out a small section to count all the species in that section, then take that information to estimate the total population for the entire forest.
Dispersion from Latin word dis- meaning “out” and spargere meaning “to scatter” - the pattern of spacing among individuals within geographic population • clumped - clustered individuals • uniform - separated by a fairly consistence distance • random - location is independent of locations of other individuals
Population Dynamics - change in size and composition over time - # of births occurring in a period of time BIRTH RATE - mortality rate; # of deaths occurring in a period of time DEATH RATE LIFE EXPECTANCY - how long an average of individual is expected to live
Age Structure - distribution of individuals among different ages in a population; young population means potential for rapid growth
Growth Rate - amount by which a populations’ size changes in a given time 4growth, shrinking, or remaining the same depends on: births deaths emigration immigration add remove remove add GROWTH RATE = BIRTH RATE – DEATH RATE if growth rate is positive if growth rate is negative - population growing - population shrinking Exponential Growth – a pattern of increase in a # due to a steady growth rate
Growth Rate Example In a certain population there is 52 births and 14 deaths per 1000 individuals in one year. Birth rate = 52/1000 Death rate = 14/1000 growth rate = 0.052 – 0.014 = 0.038 (growth per capita)
Exponential Model • J-shaped curve • population size grow slowly when small but speeds up as individuals join • predicts pop. size will increase indefinitely • does not apply to most populations • in natural environments: pops. cannot grow indef. limiting factor – anything that restrains growth
Logistic Model • S-shaped curve • builds on exponential model • takes the influencing limiting factors into account Carrying Capacity - (K); the # of individuals the environment can support over a long period of time • at carrying capacity birth & death rates are equal, growth rate stops • assumption: capacity is constant & does not fluctuate with environmental changes
Population Fluctuations Density-independent factors – reduces the population by same proportions, regardless of size Ex. weather, floods, fire Density-dependent factors – resources are limited; depends on the # of individuals in same area Ex. shortages of food or nesting sites
BottleneckModel • small populations less genetic variation
Relationships between Organisms PREDATION - an individual in one species (predator) eats all or part of an individual of another species (prey) - relationship influences size of each population and affects where and how each species live • all heterotrophs are either predators or parasites or both
natural selection favors the evolution of adaptations for finding, capturing, and consuming prey • example: • Rattlesnake – acute sense of smell and heat sensitive pits below each nostril • - can detect warm bodied prey in dark • predators survival depends on its ability to capture food, but prey’s survival depends on its ability to avoid being captured
Adaptations in Animal Prey - flee - hiding or resembling an inedible object - deceptive markings, chemical defenses (produce toxins, bright colors) mimicry – one species closely resembles another species
Adaptations in Plant Prey - cannot run away - physical defenses = sharp thorns, spines, sticky hairs, touch leaves - chemical defenses =poisonous, irritating or bad tasting
Competition • interspecific competition - 2 or more species use the same limited resource • competitive exclusion - one species is eliminated from a community because of competition for the same limited resource
Relationships between Organisms SYMBIOSIS - close, long-term relationship between 2 organism 1. parasitism - one individual is harmed while the other benefits 2. mutualism - both organisms derive some benefit 3. commensalism - one organism benefits, the other is neither helped nor harmed
Parasitism parasite – Latin word parasites meaning “one who eats t the table of another” • host is harmed • parasite benefits • does not result in immediate death of host - outside of the host ectoparasites Ex. lice, leeches, fleas, ticks, mosquitoes - inside of the host endoparasites Ex. heartworms, disease-causing protists, tapeworms
Mutualism - some relationships are so close that neither species can survive without the other • pollination – one of the most important type of mutualism • bees, butterflies, beetles, bats, & birds carry pollen between flowering plants (pollinators) • flower is a lure; color pattern, shape, scent • plant provides food (nectar or pollen)
Commensalism - one benefits the other neither harmed nor helped - scavengers are often considered to have this kind of symbiosis Example: cattle egrets and water buffalo
Ecological Succession succession – from Latin succedermeaning “to go beneath” or “to follow after” - gradual, sequential re-growth of a community of species in an area • primary succession – development of a community in an area that has not supported life previously • ex. bare rock, sand dune, island, etc • secondary succession – sequential replacement of species that follows a disruption (events that change communities, remove or destroy organisms from communities, or alters resource availability) of an existing community PIONEER SPECIES – species of organisms that predominate early in succession; tend to be small and grow quickly CLIMAX COMMUNITY – community that reaches a stable end point