In the 1940s, ecology was divided into autecology—the study of individual species in relation to the environment—and synecology—the study of groups of species in relation to the environment. The term autecology (from Ancient Greek: αὐτο, aúto, "self"; οίκος, oíkos, "household"; and λόγος, lógos, "knowledge"), refers to roughly the same field of study as concepts such as life cycles and behaviour as adaptations to the environment by individual organisms. Eugene Odum, writing in 1953, considered that synecology should be divided into population ecology, community ecology and ecosystem ecology, renaming autecology as 'species ecology' (Odum regarded "autecology" as an archaic term), thus that there were four subdivisions of ecology.[2]
Terminology
A population is defined as a group of interacting organisms of the same species. A demographic structure of a population is how populations are often quantified. The total number of individuals in a population is defined as a population size, and how dense these individuals are is defined as population density. There is also a population's geographic range, which has limits that a species can tolerate (such as temperature).
Population size can be influenced by the per capita population growth rate (rate at which the population size changes per individual in the population.) Births, deaths, emigration, and immigration rates all play a significant role in growth rate. The maximum per capita growth rate for a population is known as the intrinsic rate of increase.
In a population, carrying capacity is known as the maximum population size of the species that the environment can sustain, which is determined by resources available. In many classic population models, r is represented as the intrinsic growth rate, where K is the carrying capacity, and N0 is the initial population size.[5]
Terms used to describe natural groups of individuals in ecological studies[6]
Term
Definition
Species population
All individuals of a species.
Metapopulation
A set of spatially disjunct populations, among which there is some migration.
Population
A group of conspecific individuals that is demographically, genetically, or spatially disjunct from other groups of individuals.
Aggregation
A spatially clustered group of individuals.
Deme
A group of individuals more genetically similar to each other than to other individuals, usually with some degree of spatial isolation as well.
Local population
A group of individuals within an investigator-delimited area smaller than the geographic range of the species and often within a population (as defined above). A local population could be a disjunct population as well.
Subpopulation
An arbitrary spatially delimited subset of individuals from within a population (as defined above).
Immigration
The number of individuals that join a population over time.[7]
Emigration
The number of individuals that leave a population over time.[7]
The development of population ecology owes much to the mathematical models known as population dynamics, which were originally formulae derived from demography at the end of the 18th and beginning of 19th century.[8]
The beginning of population dynamics is widely regarded as the work of Malthus,[9] formulated as the Malthusian growth model. According to Malthus, assuming that the conditions (the environment) remain constant (ceteris paribus), a population will grow (or decline) exponentially.[8]:18 This principle provided the basis for the subsequent predictive theories, such as the demographic studies such as the work of Benjamin Gompertz and Pierre François Verhulst in the early 19th century, who refined and adjusted the Malthusian demographic model.[10]
When describing growth models, there are two main types of models that are most commonly used: exponential and logistic growth.
When the per capita rate of increase takes the same positive value regardless of population size, the graph shows exponential growth. Exponential growth takes on the assumption that there is unlimited resources and no predation. An example of exponential population growth is that of the Monk Parakeets in the United States. Originally from South America, Monk Parakeets were either released or escaped from people who owned them. These birds experienced exponential growth from the years 1975-1994 and grew about 55 times their population size from 1975. This growth is likely due to reproduction within their population, as opposed to the addition of more birds from South America (Van Bael & Prudet-Jones 1996).
When the per capita rate of increase decreases as the population increases towards the maximum limit, or carrying capacity, the graph shows logistic growth. Environmental and social variables, along with many others, impact the carrying capacity of a population, meaning that it has the ability to change (Schacht 1980).[12]
Natality or birth rate, often recruitment, which means reaching a certain size or reproductive stage. Usually refers to the age a fish can be caught and counted in nets.
Population growth rate, which measures the growth of individuals in size and length. More important in fisheries, where population is often measured in biomass.
Mortality, which includes harvest mortality and natural mortality. Natural mortality includes non-human predation, disease and old age.
If N1 is the number of individuals at time 1 then
where N0 is the number of individuals at time 0, B is the number of individuals born, D the number that died, I the number that immigrated, and E the number that emigrated between time 0 and time 1.
If we measure these rates over many time intervals, we can determine how a population's density changes over time. Immigration and emigration are present, but are usually not measured.
All of these are measured to determine the harvestable surplus, which is the number of individuals that can be harvested from a population without affecting long-term population stability or average population size. The harvest within the harvestable surplus is termed "compensatory" mortality, where the harvest deaths are substituted for the deaths that would have occurred naturally. Harvest above that level is termed "additive" mortality, because it adds to the number of deaths that would have occurred naturally. These terms are not necessarily judged as "good" and "bad," respectively, in population management. For example, a fish & game agency might aim to reduce the size of a deer population through additive mortality. Bucks might be targeted to increase buck competition, or does might be targeted to reduce reproduction and thus overall population size.
For the management of many fish and other wildlife populations, the goal is often to achieve the largest possible long-run sustainable harvest, also known as maximum sustainable yield (or MSY). Given a population dynamic model, such as any of the ones above, it is possible to calculate the population size that produces the largest harvestable surplus at equilibrium.[13] While the use of population dynamic models along with statistics and optimization to set harvest limits for fish and game is controversial among some scientists,[14] it has been shown to be more effective than the use of human judgment in computer experiments where both incorrect models and natural resource management students competed to maximize yield in two hypothetical fisheries.[15][16] To give an example of a non-intuitive result, fisheries produce more fish when there is a nearby refuge from human predation in the form of a nature reserve, resulting in higher catches than if the whole area was open to fishing.[17][18]
At its most elementary level, interspecific competition involves two species utilizing a similar resource. It rapidly gets more complicated, but stripping the phenomenon of all its complications, this is the basic principle: two consumers consuming the same resource.[19]:222
An important concept in population ecology is the r/K selection theory. For example, if an animal has the choice of producing one or a few offspring, or to put a lot of effort or little effort in offspring—these are all examples of trade-offs. In order for species to thrive, they must choose what is best for them, leading to a clear distinction between r and K selected species.[20]
The first variable is r (the intrinsic rate of natural increase in population size, density independent) and the second variable is K (the carrying capacity of a population, density dependent).[21] It is important to understand the difference between density-independent factors when selecting the intrinsic rate [find another article relating to the intrinsic rate] and density-dependent when selection the carrying capacity. Carrying capacity is only found during a density-dependent population. Density-dependent factors influence the carrying capacity are predation, harvest, and genetics, so when selecting the carrying capacity it is important to understand to look at the predation or harvest rates that influence the population (Stewart 2004). An r-selected species (e.g., many kinds of insects, such as aphids[22]) is one that has high rates of fecundity, low levels of parental investment in the young, and high rates of mortality before individuals reach maturity. Evolution favors productivity in r-selected species.
In contrast, a K-selected species (such as humans) has low rates of fecundity, high levels of parental investment in the young, and low rates of mortality as individuals mature. Evolution in K-selected species favors efficiency in the conversion of more resources into fewer offspring.[23][24] K-selected species generally experience stronger competition, where populations generally live near carrying capacity. These species have heavy investment in offspring, resulting in longer lived organisms, and longer period of maturation. Offspring of K-selected species generally have a higher probability of survival, due to heavy parental care and nurturing.[20]
Offspring Quality
The offspring fitness is mainly affected by the size and quality of that specific offspring [depending on the species]. Factors that contribute to the relative fitness of offspring size is either the resources the parents provide to their young or morphological traits that come from the parents. The overall success of the offspring after the initial birth or hatching is the survival of the young, the growth rate, and the birthing success of the offspring. There is found to be no effect of the young being raised by the natural parents or foster parents, the offspring need the proper resources to survive (Kristi 2010).
A study that was conducted on the egg size and offspring quality in birds found that, in summary, that the egg size contributes to the overall fitness of the offspring. This study shows the direct relationship to the survivorship curve Type I in that if the offspring is cared for during its early stages of life by a parent, it will die off later in life. However, if the offspring is not cared for by the parents due to an increase in egg quantity, then the survivorship curve will be similar to Type III, in that the offspring will die off early and will survive later in life.
In some populations, organisms in lower trophic levels are controlled by organisms at the top. This is known as top-down control.
For example, the presence of top carnivores keep herbivore populations in check. If there were no top carnivores in the ecosystem, then herbivore populations would rapidly increase, leading to all plants being eaten. This ecosystem would eventually collapse.[25]
Bottom-up controls
Bottom-up controls, on the other hand, are driven by producers in the ecosystem. If plant populations change, then the population of all species would be impacted.
For example, if plant populations decreased significantly, the herbivore populations would decrease, which would lead to a carnivore population decreasing too. Therefore, if all of the plants disappeared, then the ecosystem would collapse. Another example would be if there were too many plants available, then two herbivore populations may compete for the same food. The competition would lead to an eventual removal of one population.[25]
Do all ecosystems have to be either top-down or bottom-up?
An ecosystem does not have to be either top-down or bottom-up. There are occasions where an ecosystem could be bottom-up sometimes, such as a marine ecosystem, but then have periods of top-down control due to fishing.[26]
Survivorship curves are graphs that show the distribution of survivors in a population according to age. Survivorship curves play an important role in comparing generations, populations, or even different species.[27]
A Type I survivorship curve is characterized by the fact that death occurs in the later years of an organism's life (mostly mammals). In other words, most organisms reach the maximum expected lifespan and the life expectancy and the age of death go hand-in-hand (Demetrius 1978). Typically, Type I survivorship curves characterize K-selected species.
Type II survivorship shows that death at any age is equally probable. This means that the chances of death are not dependent on or affected by the age of that organism.
Type III curves indicate few surviving the younger years, but after a certain age, individuals are much more likely to survive. Type III survivorship typically characterizes r-selected species.[28]
Populations are also studied and conceptualized through the "metapopulation" concept. The metapopulation concept was introduced in 1969:[29]
"as a population of populations which go extinct locally and recolonize."[30]:105
Metapopulation ecology is a simplified model of the landscape into patches of varying levels of quality.[31] Patches are either occupied or they are not. Migrants moving among the patches are structured into metapopulations either as sources or sinks. Source patches are productive sites that generate a seasonal supply of migrants to other patch locations. Sink patches are unproductive sites that only receive migrants. In metapopulation terminology there are emigrants (individuals that leave a patch) and immigrants (individuals that move into a patch). Metapopulation models examine patch dynamics over time to answer questions about spatial and demographic ecology. An important concept in metapopulation ecology is the rescue effect, where small patches of lower quality (i.e., sinks) are maintained by a seasonal influx of new immigrants. Metapopulation structure evolves from year to year, where some patches are sinks, such as dry years, and become sources when conditions are more favorable. Ecologists utilize a mixture of computer models and field studies to explain metapopulation structure.[32]
Metapopulation ecology allows for ecologists to take in a wide range of factors when examining a metapopulation like genetics, the bottle-neck effect, and many more. Metapopulation data is extremely useful in understanding population dynamics as most species are not numerous and require specific resources from their habitats. In addition, metapopulation ecology allows for a deeper understanding of the effects of habitat loss, and can help to predict the future of a habitat. To elaborate, metapopulation ecology assumes that, before a habitat becomes uninhabitable, the species in it will emigrate out, or die off. This information is helpful to ecologists in determining what, if anything, can be done to aid a declining habitat. Overall, the information that metapopulation ecology provides is useful to ecologists in many ways (Hanski 1998).
Journals
The first journal publication of the Society of Population Ecology, titled Population Ecology (originally called Researches on Population Ecology) was released in 1952.[33]
Ecology is the natural science of the relationships among living organisms, including humans, and their physical environment. Ecology considers organisms at the individual, population, community, ecosystem, and biosphere level. Ecology overlaps with the closely related sciences of biogeography, evolutionary biology, genetics, ethology, and natural history.
Theoretical ecology is the scientific discipline devoted to the study of ecological systems using theoretical methods such as simple conceptual models, mathematical models, computational simulations, and advanced data analysis. Effective models improve understanding of the natural world by revealing how the dynamics of species populations are often based on fundamental biological conditions and processes. Further, the field aims to unify a diverse range of empirical observations by assuming that common, mechanistic processes generate observable phenomena across species and ecological environments. Based on biologically realistic assumptions, theoretical ecologists are able to uncover novel, non-intuitive insights about natural processes. Theoretical results are often verified by empirical and observational studies, revealing the power of theoretical methods in both predicting and understanding the noisy, diverse biological world.
The carrying capacity of an environment is the maximum population size of a biological species that can be sustained by that specific environment, given the food, habitat, water, and other resources available. The carrying capacity is defined as the environment's maximal load, which in population ecology corresponds to the population equilibrium, when the number of deaths in a population equals the number of births. The effect of carrying capacity on population dynamics is modelled with a logistic function. Carrying capacity is applied to the maximum population an environment can support in ecology, agriculture and fisheries. The term carrying capacity has been applied to a few different processes in the past before finally being applied to population limits in the 1950s. The notion of carrying capacity for humans is covered by the notion of sustainable population.
This glossary of ecology is a list of definitions of terms and concepts in ecology and related fields. For more specific definitions from other glossaries related to ecology, see Glossary of biology, Glossary of evolutionary biology, and Glossary of environmental science.
In population ecology and economics, maximum sustainable yield (MSY) is theoretically, the largest yield that can be taken from a species' stock over an indefinite period. Fundamental to the notion of sustainable harvest, the concept of MSY aims to maintain the population size at the point of maximum growth rate by harvesting the individuals that would normally be added to the population, allowing the population to continue to be productive indefinitely. Under the assumption of logistic growth, resource limitation does not constrain individuals' reproductive rates when populations are small, but because there are few individuals, the overall yield is small. At intermediate population densities, also represented by half the carrying capacity, individuals are able to breed to their maximum rate. At this point, called the maximum sustainable yield, there is a surplus of individuals that can be harvested because growth of the population is at its maximum point due to the large number of reproducing individuals. Above this point, density dependent factors increasingly limit breeding until the population reaches carrying capacity. At this point, there are no surplus individuals to be harvested and yield drops to zero. The maximum sustainable yield is usually higher than the optimum sustainable yield and maximum economic yield.
Population dynamics is the type of mathematics used to model and study the size and age composition of populations as dynamical systems.
The metabolic theory of ecology (MTE) is the ecological component of the more general Metabolic Scaling Theory and Kleiber's law. It posits that the metabolic rate of organisms is the fundamental biological rate that governs most observed patterns in ecology. MTE is part of a larger set of theory known as metabolic scaling theory that attempts to provide a unified theory for the importance of metabolism in driving pattern and process in biology from the level of cells all the way to the biosphere.
Biological dispersal refers to both the movement of individuals from their birth site to their breeding site, as well as the movement from one breeding site to another . Dispersal is also used to describe the movement of propagules such as seeds and spores. Technically, dispersal is defined as any movement that has the potential to lead to gene flow. The act of dispersal involves three phases: departure, transfer, settlement and there are different fitness costs and benefits associated with each of these phases. Through simply moving from one habitat patch to another, the dispersal of an individual has consequences not only for individual fitness, but also for population dynamics, population genetics, and species distribution. Understanding dispersal and the consequences both for evolutionary strategies at a species level, and for processes at an ecosystem level, requires understanding on the type of dispersal, the dispersal range of a given species, and the dispersal mechanisms involved. Biological dispersal can be correlated to population density. The range of variations of a species' location determines expansion range.
A metapopulation consists of a group of spatially separated populations of the same species which interact at some level. The term metapopulation was coined by Richard Levins in 1969 to describe a model of population dynamics of insect pests in agricultural fields, but the idea has been most broadly applied to species in naturally or artificially fragmented habitats. In Levins' own words, it consists of "a population of populations".
The Allee effect is a phenomenon in biology characterized by a correlation between population size or density and the mean individual fitness of a population or species.
In ecology, r/K selection theory relates to the selection of combinations of traits in an organism that trade off between quantity and quality of offspring. The focus on either an increased quantity of offspring at the expense of individual parental investment of r-strategists, or on a reduced quantity of offspring with a corresponding increased parental investment of K-strategists, varies widely, seemingly to promote success in particular environments. The concepts of quantity or quality offspring are sometimes referred to as "cheap" or "expensive", a comment on the expendable nature of the offspring and parental commitment made. The stability of the environment can predict if many expendable offspring are made or if fewer offspring of higher quality would lead to higher reproductive success. An unstable environment would encourage the parent to make many offspring, because the likelihood of all of them surviving to adulthood is slim. In contrast, more stable environments allow parents to confidently invest in one offspring because they are more likely to survive to adulthood.
Intraspecific competition is an interaction in population ecology, whereby members of the same species compete for limited resources. This leads to a reduction in fitness for both individuals, but the more fit individual survives and is able to reproduce. By contrast, interspecific competition occurs when members of different species compete for a shared resource. Members of the same species have rather similar requirements for resources, whereas different species have a smaller contested resource overlap, resulting in intraspecific competition generally being a stronger force than interspecific competition.
The Gompertz curve or Gompertz function is a type of mathematical model for a time series, named after Benjamin Gompertz (1779–1865). It is a sigmoid function which describes growth as being slowest at the start and end of a given time period. The right-side or future value asymptote of the function is approached much more gradually by the curve than the left-side or lower valued asymptote. This is in contrast to the simple logistic function in which both asymptotes are approached by the curve symmetrically. It is a special case of the generalised logistic function. The function was originally designed to describe human mortality, but since has been modified to be applied in biology, with regard to detailing populations.
Life history theory (LHT) is an analytical framework designed to study the diversity of life history strategies used by different organisms throughout the world, as well as the causes and results of the variation in their life cycles. It is a theory of biological evolution that seeks to explain aspects of organisms' anatomy and behavior by reference to the way that their life histories—including their reproductive development and behaviors, post-reproductive behaviors, and lifespan —have been shaped by natural selection. A life history strategy is the "age- and stage-specific patterns" and timing of events that make up an organism's life, such as birth, weaning, maturation, death, etc. These events, notably juvenile development, age of sexual maturity, first reproduction, number of offspring and level of parental investment, senescence and death, depend on the physical and ecological environment of the organism.
In landscape ecology, landscape connectivity is, broadly, "the degree to which the landscape facilitates or impedes movement among resource patches". Alternatively, connectivity may be a continuous property of the landscape and independent of patches and paths. Connectivity includes both structural connectivity and functional connectivity. Functional connectivity includes actual connectivity and potential connectivity in which movement paths are estimated using the life-history data.
Source–sink dynamics is a theoretical model used by ecologists to describe how variation in habitat quality may affect the population growth or decline of organisms.
A survivorship curve is a graph showing the number or proportion of individuals surviving to each age for a given species or group. Survivorship curves can be constructed for a given cohort based on a life table.
A fishery is an area with an associated fish or aquatic population which is harvested for its commercial or recreational value. Fisheries can be wild or farmed. Population dynamics describes the ways in which a given population grows and shrinks over time, as controlled by birth, death, and migration. It is the basis for understanding changing fishery patterns and issues such as habitat destruction, predation and optimal harvesting rates. The population dynamics of fisheries is used by fisheries scientists to determine sustainable yields.
The paradox of the pesticides is a paradox that states that applying pesticide to a pest may end up increasing the abundance of the pest if the pesticide upsets natural predator–prey dynamics in the ecosystem.
Semelparity and iteroparity are two contrasting reproductive strategies available to living organisms. A species is considered semelparous if it is characterized by a single reproductive episode before death, and iteroparous if it is characterized by multiple reproductive cycles over the course of its lifetime. Iteroparity can be further divided into continuous iteroparity and seasonal iteroparity Some botanists use the parallel terms monocarpy and polycarpy.
↑ Holden, Matthew H; Ellner, Stephen P (2016). "Human judgment vs. Quantitative models for the management of ecological resources". Ecological Applications. 26 (5): 1553–1565. arXiv:1603.04518. doi:10.1890/15-1295. PMID27755756. S2CID1279459.
↑ Vandermeer, J. H.; Goldberg, D. E. (2003). Population ecology: First principles. Woodstock, Oxfordshire: Princeton University Press. ISBN978-0-691-11440-8.
↑ Whitham, T. G. (1978). "Habitat Selection by Pemphigus Aphids in Response to Response Limitation and Competition". Ecology. 59 (6): 1164–1176. doi:10.2307/1938230. JSTOR1938230.
↑ MacArthur, R.; Wilson, E. O. (1967). "The Theory of Island Biogeography". Princeton, NJ: Princeton University Press.{{cite journal}}: Cite journal requires |journal= (help)
↑ Pianka, E. R. (1972). "r and K Selection or b and d Selection?". The American Naturalist. 106 (951): 581–588. doi:10.1086/282798. S2CID83947445.
Henderson, Kirsten; Loreau, Michel (2019). "An ecological theory of changing human population dynamics". Kirsten Henderson (Centre for Biodiversity, Theory, and Modelling, Theoretical and Experimental Ecology Station, CNRS, Moulis, France) and Michel Loreau. 1. People and Nature, British Ecological Society: 31–43. doi:10.1002/pan3.8.
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