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What you’ll learn to do: Discuss the scope and study of population ecology

Imagine sailing down a river in a small motorboat on a weekend afternoon; the water is smooth and you are enjoying the warm sunshine and cool breeze when suddenly you are hit in the head by a 20-pound silver carp. This is a risk now on many rivers and canal systems in Illinois and Missouri because of the presence of Asian carp.

This fish—actually a group of species including the silver, black, grass, and big head carp—has been farmed and eaten in China for over 1000 years. It is one of the most important aquaculture food resources worldwide. In the United States, however, Asian carp is considered a dangerous invasive species that disrupts community structure and composition to the point of threatening native species.

Introduction to Population Ecology

The first significant contribution to the theory of population ecology was that of Thomas Malthus, an English clergyman, who in 1798 published his Essay on the Principle of Population. Malthus introduced the concept that at some point in time an expanding population must exceed supply of prerequisite natural resources, i.e., population increases exponentially resulting in increasing competition for means of subsistence, food, shelter, etc. This concept has been termed the "Struggle for Existence".

Charles Darwin

Malthus's theories profoundly influenced Charles Darwin 1859, On the Origin of Species, e.g., the concept of "Survival of the Fittest". Mortality of this type can be termed "facultative mortality" (as opposed to catastrophic mortality, e.g., weather, insecticides).

Harry Smith, pioneering biological control worker with the University of California (1935), proposed the equivalent and now accepted terms density-dependent and density-independent. Density-dependent mortality factors are those that are facultative in effect, density-independent mortality factors are those that are catastrophic in effect.

A density-dependent mortality factor is one that causes a varying degree of mortality in subject population,and that the degree of mortality caused in a function (i.e., related) to the density of the subject (affected) population (density-geared, feedback regulation, self-regulating or self-limiting) may and typically involves a lag effect., e.g., most biological control agents.

Figure 1. Cycles in the population dynamics of the snowshoe hare and its predator the Canadian lynx (redrawn from MacLulich 1937). Note that percent mortality is an elusive measure, it may, or may not, be useful since mortality varies with environment and time.

Figure 2A. Logistic growth (Nt = Nt-1 + Rm(1-Nt-1/K)Nt-1). N = equal population density at a given time (t). This so-called "logistic equation" was first proposed by the mathematician Verhulst (1839). In ecology texts this equation is more often written as DN/dt = rm(1-N/K)N, where D is density at any given time (t). K = carrying capacity of environment. Rm = loge(Rm + 1).

Royal N. Chapman, Univ. Minnesota, in the 1930s proposed the concept of a balance between biotic potential and environmental resistance. Chapman`s model was a mathematical representation of the Malthusian concept, illustrated here by the logistic growth of a laboratory population of yeast cells. Population growth trajectory (N1 = N0 + (Rm -sN0)N0 ) Rm = maximum rate of increase, here = 1, s = interaction coefficient, here = 0,0001, and carrying capacity of environment = 1000.

Figure 2B. Population growth (N1 = N0 + RN0), where N1 = 10 and R=0.5 (blue), R=0 (black), and R=-0.5 (red).

Human populations represent another example of exponential growth. Magnitude of the problems posed by human population growth can be seen from the fact that it took more than 1 million years for the human population to first reach 200,000 (the current daily rate of increase (See: US Census, Historical Estimates of World Population). The human population is estimated to have first reached 1 billion persons in 1830, and 2 billion in 1930, a doubling time of 100 years. In 1960, thirty years later, the population edged past 3 billion, and a mere 15 years later, 4 billion. In 1986, we exceeded 5 billion for the first time. Despite a slowing of the growth rate, it is expected that the human population will exceed 6 billion in early 1999 (see: University ofNorth Carolina, Chapel Hill World Population Counter) . To feed this population, only as well as we presently do, it will be necessary to increase food production 20% over the next 10-15 years.


1 billion
2 billion
3 billion
4 billion
5 billion
6 billion
7 billion
8 billion
9 billion
(range of estimates: 10.4-17 billion)

Exercise: Compute annual population growth rates for each of the time perioids above:

Equation for population growth model is X=X0ert where the original population is X0 mathematical constant: natural log (e = 2.718), represents Malthusian parameter. Population will increase in size to X, over time (t), if rate of increase (r) is positive. If population not growing, i.e., r = 0.0, then rt = 0.0, and e0.0= l.0, X = X0. When r has a value greater than 0 population will increase, e.g., rt = 0.693 (e0.693 = 2.0), population will double in time t (X = 2X0). The doubling time of this population will be t = 0.693/r. If the population is decreasing, r is a negative value. The function of X = X0ert can be made a straight line by the natural log transformation, i.e., lnX = lnX0 + rt (the equation for a straight line). Characteristics of this line are: an intercept at lnX0 and a slope of r. Linear regression analysis can be applied (since this is a straight line), with the independent variable being time. The linear equation thus describes the rate of population growth (+) or decline (-). Algebraic rearrangement of this equation permits one to solve for the rate of population increase.

In the 1920s, A. J. Lotka (1925) and V. Volterra (1926) devised mathematical models representing host/prey interaction. This was the first attempt to mathematically represent a population model as achieving a cyclic balance in mean mean (characteristic) population density, i.e., to attain a dynamic equilibrium. The Lotka-Volterra curve assumes that prey destruction is a function not only of natural enemy numbers, but also of prey density, i.e., related to the chance of encounter. Populations of prey and predator were predicted to flucuate in a regular manner (Volterra termed this "the law of periodic cycle"). Lotka-Volterra model is an oversimplification of reality, as these curves are derived from infinitesimal calculus when in nature association is seldom continuous over time (life cycles being finite).

Figure 4A. Steady-state population model (N1 = N0 + Rm(1 -sN0 /K)N0, where Rm = 2, K = 1000, and intitial displacement from equilibrium x = -10.

Figure 4B (top). Steady-state population model. (N1 = N0 + Rm(1 -sN0 /K)N0 ), when K = 1000, Rm = 3 and initial displacement from equilibrium x = -10.
Figure 4C (bottom). Steady-state population model. (N1 = N0 + Rm(1 -sN0 /K)N0 ), when K = 1000, Rm = 1.5 and initial displacement from equilibrium x = -10.

A. J. Nicholson (Australian entomologist) was a leading proponent of concept of density-dependent mortality factors. He maintained that density-dependent mortality played the key role in regulating prey populations. This is the essence of the so-called "Balance of Nature" theory. This theory implied a static balance about a mean (characteristic) equilibrium density with reciprocal (feedback) oscillations in density about these means.

Nicholson and V. A. Bailey (1935) proposed a population model that incorporated a "lag effect". This is particularly appropriate to parasitoids were population effects of attack (oviposition) may not be evident until the parasitoid has completed its immature development and emerges as a adult (killing the host).

Leading proponents of this view of population dynamics included the early California biological control workers. The theory and practice of biological control can be said to revolve about this assumption.

However, a contrary view of the nature of population regulating mortality factors was argued by others, especially W. R. Thompson (Dominion Parasite Laboratory). The Canadian workers held that assumptions of Nicholson and like thinkers were unrealistic, and did not occur in nature, i.e., that the regulating role of a so- called density-dependent mortality factors was largely myth. These workers argued that it was unnecessary to postulate such a mechanism of population regulation. They observed that the environment never remains continually favorable or unfavorable for any species. If it did so that population would inevitably become either infinite or decline to extinction. They maintained it was more accurate to say that populations were (in reality) always in a state of "dynamic equilibrium" with their environment.

H. G. Andrewartha and L. C. Birch were leading proponents of the concept that populations could be, and often are, regulated by abiotic factors.

These arguments became heated in the mid-1950s and early 1960s. Much of the confusion and controversy regarding mechanisms of population regulation stemmed from an inadequate data base, but an even more confining limitation was the essential impracticality of making the extremely complex calculations required to manipulate such data. Accordingly rapid advances in theoretical ecology, especially in the area of population ecology, only occurred with the introduction of high speed computers and the refinement of statistical theory.

Much of early population theory was developed deductively from controlled laboratory experiments or fragmented field observations. This resulted in a tendency to oversimplification and the development of models often not reflecting biological reality.

One of the most useful starting points for a population ecologist is the development of a life table. A life table is a schedule of mortality for each cohort (age group) of individuals in the population. The methods were developed originally for actuarial or demographic studies. Multifactor studies which incorporated the life table technique were once largely the province of forest entomologists, but are now widely used in agriculture.

The final test of any population model is its usefulness to predict (generation to generation) changes in abundance or to explain why changes occur at particular population densities.

Consequences of recent advances in understanding of population dynamics has lead to almost universal (among ecologists) acceptance of the proposition that population growth is geared to population density.

Differences in the relative importance of density-dependent and density-independent mortality factors varies in different environments, e.g., the role of biotic components tends to be greater in more stable (benign) environments.

Competitive processes/cooperative processes: we often think of interactions between individuals even within species as only negative, but interactions can be positive (even between species), e.g., defense against predators, genetic diversity (concept of minimum density), mate finding (sustainable population), early mortality may favor subsequent survival.

Interactions between species can be very complex even when only 2 species are considered (through impact on environment of other species). Each species can affect environment of other positively (+), negatively (-), or have no effect (0). Major categories include: mutualism (++), commensualism (+0), predator/prey (+-), competition (- -), and amensalism (rare) (-0).

Insects and plants of two types: 1) good colonizers, e.g., weed species, with high reproductive potential (capacity), adaptable, invaders, readily dispersed, "r-strategists" 2) good competitors, high survival, tend to stable population (K = equilibrium), exploit stable environments, win out in competition, "K-strategists" (R. H. MacArthur and E. O. Wilson 1967).

Most crop pests are r-strategists, e.g., aphids and phytophagous insects in general. Natural enemies, i.e., parasites and predators, are mostly K strategists. This is said to be one reason for the high failure rate associated with introductions of exotic natural enemies.

Most crop plants are early succession plants, i.e., they are weedy species and accordingly they also are r-strategists. The r-selected species are particularly suited to exploiting the ecological patchiness and instability of the agroecosystem.

Figure 5A (top) and 5B (bottom). Island Biogeography: (MacArthur and Wilson 1967)

Equilibrium models for near and distant islands. Equilibrium (in number of species present) occurs where curves of rates of immigration and rates of extinction intersect. I is the initial rate of immigration and P is the total number in the species pool on the mainland.

The parallel between agroecosystems and island defaunation is obvious. Many factors affect the various population processes: number of potential invaders, distance of source of invaders, conditions for invasion and settling, attractiveness (favorability) of crop.

Effects of various regulating factors on the population dynamics of the host tend to differ: predators, harmonic (cyclic), parasitoids, intrusive, pathogens, disruptive, food, catastrophic (W. J. Turnock and J. A. Muldrew 1971).

Numerical response is the key to the success of entomophagous insects occurs in the following ways:

  1. Concentration, not different from sigmoid curve of functional response.
  2. Immediate numerical response, increased survival
  3. Delayed numerical response, increased reproduction.

Figure 6A (top) and 6B (bottom). Carl B. Huffaker et al. 1968 graphically presented four postulated types of functional (behavioral) responses of predators including entomophagous insects to prey density. (A) number killed, (B) percent killed. After Huffaker et al. 1968.

Nicholson curve: number of attacks determined by searching capacity (i.e., density-dependent). C. S. Holling (1965) disk curve: characteristic of invertebrate predators. Sigmoid curve: characteristic of vertebrate predators. Thompson curve: number of attacks limited by capacity for consumption or production of eggs, but not by searching capacity or host density.

Experimental data suggests that Holling's disc curve is characteristic of the predatory behavior of most entomophagous insects, i.e., the number of prey attacked increases but at a proportionately slower rate as prey density increases.

Interactions between species, especially between predators and prey are of great theoretical and practical interest to ecologists.

Environmental feedbacks: Populations degrade their environment, utilizing its resources. If the environment is highly favorable, resources are not limiting, i.e., the resources are replaced or recover faster than they are utilized. This favors rapid (exponential) growth of the population. As the rate of utilization of resources approaches the rate of replacement, the rate of population increase slows. Finally, population overshots carrying capacity of environment (resources depleted faster than can be renewed). This results in severe competition and the population collapses. When the population drops below the replacement value the environment recovers.

Figure 7 (above). A reproduction plane divided into zones of population growth (R > 0) and decline (R < 0) by the equilibrium diagonal line (R = 0). The density of the population at equilibrium (K) changes in direction to the favorability of the environment (F). The equilibrum line is further divided into 3 sections with different stability properties: 1) a lower section where sK <1 providing asymptomic stability, a midsection where 1 < sK < 2 providing dampened stability, and an upper section sK>2 which is unstable.

Figure 8A (above). A population trajectory on its reproduction plane showing growth over three time increments (N0 to N3) in a consistent envrionment and also following environmental degradation (broken line) at the end of the second time period. The critical density (Nc, here shown as red line) is where the population utilizes resources at the same rate that they are renewed (replaced), for a given degree of environmental favorability.

Figure 8B (above). A population trajectory on its reproduction plane showing growth over three time increments (N0 to N3) in a consistent environment and also following environmental degradation (broken line) at the end of the second time period.

Figure 9A-C (below). Predator/prey interactions (figures redrawn from Berryman, 1981)

Figure 9A. Reproduction plane for a prey species (A), where Ka is the carrying capacity in the absence of predation, Wb is the marginal cost of predation, Pb is the predator density which drives the prey to extinction.

Figure 9B. Reproduction plane for a predatorspecies (B), where Pa is the minimal prey density needed to sustain a predator population, and Qa is the marginal benefit of the prey.

Figure 9C. Reproduction plane for a prey species (A) and superimposed with a particular dynamic tragectory. An infinite number of curves could be drawn and the relationships need not be straight lines. The stability of the relationship would depend upon the characteristics of the curves.

Interactions (reproduction planes) between predator and prey. There must be some prey to sustain the predator. Pb is the predator density which drives prey to extinction. Ka is the carrying capacity in the absence of the predator. Wb is the marginal cost of a given level of predation. Pa is the minimum prey density required to sustain the predator population (and avoid extinction). Qa is the marginal benefit of prey. The superimposed reproduction planes show equilibrium lines for predator, Eb, and prey, Ea, and a particular dynamic trajectory.

We can draw an infinite variety of these curves, relationships not necessarily straight line, stability will depend on characteristic of curves (assuming these represent real life situation).

Community stability: A central tenet of classical ecology is that complex communities tend to be more stable (largely based on observation) theory recently challenged, argument that simple systems may be less subject to external disturbances. What has emerged is that:

  1. Competitive interactions between species lead to instability unless dominated by negative feedbacks within self-loops, i.e., one species setting in motion cyclic oscillations in numbers of another.
  2. The number of competing species increase the competitive interactions must be proportionately weaker or instability will result.
  3. Interactions between tropic levels (predator/prey) tend to stabilize populations (community).
  4. Community stability is frequently interrupted by severe environmental disruptions, leading to a series of successional communities gradually evolving to climax associations. Frequent or continual disruptions may lead to persistent nonclimax community. Herbivores play an important role in plant succession by tending to harvest unthrifty members of a plant community, e.g., overmature trees. They also recycle nutrients and increase productivity and vigor of community, - mutualistic?

Population dynamics/epidemiology theory is a vast and formidable subject. However, the synoptic model developed by T. R. E. Southwood (1975 and subsequent papers) is most instructive, and summarizes much of the theoretical concepts and empirical bases for contemporary model building.

The model has 3 salient features:

  1. Natality (birthrate) is low at low population densities because of problems associated with low densities, e.g., finding mates, increases as population increases, peaks and finally declines as intraspecific competition increases, e.g., competition for food.
  2. Predation increases with increasing host (herbivore) density, then declines as host populations overwhelm (and escape) their regulating influence. This occurs because the characteristic pattern is for overall predator response to be sigmoid, based on a) functional response of the individual predator and b) numerical response of the population.
  3. Intraspecific competition increases with increased population (prey) density. This produces additional mortality as natality shows a down-turn. Other density-dependent mortality and stress also comes into play producing a marked increase in combined mortality.

Figure 10. Generalized relationship between population density of a herbivore species, natality, mortality caused by enemies (with a peak at moderatly low low population density) and intraspecific competition (with a peak at relatively high population density) (after Southwood 1975).

Figure 11. Generalized relationship between herbivore population density in one generation and herbivore population density in the next generation. The line at 45 degrees is the line of no growth, i.e., population density stable from one generation to the next. Points above the line indicate population growth, those below the line population decline. X = extinction point, S = stable equilibrium point, R = point of release from natural enemies, O = oscillations equilibrium point, and C = crash point.

Figure 13 (above). Synoptic model of population growth (after Southwood and Comins 1976, J. Anim. Ecol. 45: 949-965). The synoptic model of Southwood demonstrates the link between habitat stability (natural ecosystems evolving toward a K-selected type, agroecosystems representing an r-selected type) and relative favorability of each for pests and natural control agents. Pests having a relative advantage in r-selected habitats, while natural enemies tend to dominance in more stable ecosystems.

Common feature of epidemics (epizootics) is that outward migration (emigration) occurs advancing in waves. Knowledge of spatial distributions and population dynamics can be used to manage populations over large areas.

Simulation games have been used to study and test ecological theory. One such model is the so-called "Game of Life". This is a game invented by a mathematician to illustrate (mimic) environmental feedback loops, a number of individuals (checkers) are positioned at random on board. Rules are that any individual adjacent to one or more neighbors dies of isolation and any adjacent to four or more individuals dies of overcrowding (two negative feedbacks) and that whenever an empty square exists adjacent to exactly three individuals, a new individual is born (a parody of real-life).

The population dynamics of pests occurring over large areas can be investigated by gridding the area and monitoring population trends, studies of dispersal (migration) reproduction, competition, weather, environmental conditions, etc.

Tactics and Strategies:

Pest management is as applied science with no unique principles. Focus of all pest management programs is to "erode the homeostatic capability" ("homeostasis") of pest populations i.e., to reduce the equilibrium position of populations (K) spatially and temporally so that the frequency and duration of fluctuation above economic thresholds are reduced or eliminated.

The tactics (ecological manipulations) and strategies (pest management decision-making processes) distinguish pest management (IPM) from unilateral approaches.

Pest management is the selection, integration, and implementation of pest control strategies on the basis of predicted economic, ecological, and sociological consequences (Rabb 1972).

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"This is refreshing because so many population biology books seem content to dwell upon the mathematical satisfaction that can be derived from elegant models. Some of Rockwell's chapters, such as the one on metapopulations, send the reader to a selection of case studies illustrating the application of a particular concept or model. This enables the student to compare theory with actuality and thereby assess the theory more critically. In this respect, it is truly a text of population ecology rather than just population biology." Bulletin of the British Ecological Society

"Introduction of Population Ecology is an accessible and up-to-date textbook covering all aspects of population ecology . . . This text is an essential introduction to population ecology, including those with little mathematical experience." Biotechnology, Agronomy, Society and Environment

"This is an eminently readable text ideal for a University audience and would not be out of place in a school library to extend able students."
Journal of Biological Education

“Written clearly and succinctly for beginners, [this] exciting and well-presented book also has practical implications for policy makers, conservationists…and stewards of the natural habitat.”
Northeastern Naturalist

From the Back Cover

Each chapter provides an overview of how population theory has developed, exploring single-species population growth and self-limitation, metapopulations, and a broad range of interspecific interactions including parasite–host, predator–prey, and plant–herbivore. Throughout, the mathematics is kept as simple as possible, using a careful step-by-step approach, and including graphs and other visual aids to help understanding. Sample simulations can be found at

This text is an essential introduction to population ecology for undergraduate and graduate students taking courses in population ecology, including those with little mathematical experience. Introduction to Population Ecology - Biology

Imagine sailing down a river in a small motorboat on a weekend afternoon the water is smooth and you are enjoying the warm sunshine and cool breeze when suddenly you are hit in the head by a 20-pound silver carp. This is a risk now on many rivers and canal systems in Illinois and Missouri because of the presence of Asian carp.

Figure 1. Asian carp jump out of the water in response to electrofishing. The Asian carp in the inset photograph were harvested from the Little Calumet River in Illinois in May, 2010, using rotenone, a toxin often used as an insecticide, in an effort to learn more about the population of the species. (credit main image: modification of work by USGS credit inset: modification of work by Lt. David French, USCG)

This fish—actually a group of species including the silver, black, grass, and big head carp—has been farmed and eaten in China for over 1000 years. It is one of the most important aquaculture food resources worldwide. In the United States, however, Asian carp is considered a dangerous invasive species that disrupts community structure and composition to the point of threatening native species.


There are a variety of approaches to species reintroduction. The optimal strategy will depend on the biology of the organism. [4] The first matter to address when beginning a species reintroduction is whether to source individuals in situ, from wild populations, or ex situ, from captivity in a zoo or botanic garden, for example.

In situ sourcing Edit

In situ sourcing for restorations involves moving individuals from an existing wild population to a new site where the species was formerly extirpated. Ideally, populations should be sourced in situ when possible due to the numerous risks associated with reintroducing organisms from captive populations to the wild. [5] To ensure that reintroduced populations have the best chance of surviving and reproducing, individuals should be sourced from populations that genetically and ecologically resemble the recipient population. [6] Generally, sourcing from populations with similar environmental conditions to the reintroduction site will maximize the chance that reintroduced individuals are well adapted to the habitat of the reintroduction site . [7] [6]

One consideration for in situ sourcing is at which life stage the organisms should be collected, transported, and reintroduced. For instance, with plants, it is often ideal to transport them as seeds as they have the best chance of surviving translocation at this stage. However, some plants are difficult to establish as seed and may need to be translocated as juveniles or adults. [4]

Ex situ sourcing Edit

In situations where in situ collection of individuals is not feasible, such as for rare and endangered species with too few individuals existing in the wild, ex situ collection possible. Ex situ collection methods allow storage of individuals that have high potential for reintroduction. Storage examples include germplasm stored in seed banks, sperm and egg banks, cryopreservation, and tissue culture. [5] Methods that allow for storage of a high numbers of individuals also aim to maximize genetic diversity. Stored materials generally have long lifespans in storage, but some species do lose viability when stored as seed. [8] Tissue culture and cryopreservation techniques have only been perfected for a few species. [9]

Organisms may also be kept in living collections in captivity. Living collections are more costly than storing germplasm and hence can support only a fraction of the individuals that ex situ sourcing can. [5] Risk increases when sourcing individuals to add to living collections. Loss of genetic diversity is a concern because fewer individuals stored. [10] Individuals may also become genetically adapted to captivity, which often adversely affects the reproductive fitness of individuals. Adaptation to captivity may make individuals less suitable for reintroduction to the wild. Thus, efforts should be made to replicate wild conditions and minimize time spent in captivity whenever possible. [11] [12]

Reintroduction biology is a relatively young discipline and continues to be a work in progress. No strict and accepted definition of reintroduction success exists, but it has been proposed that the criteria widely used to assess the conservation status of endangered taxa, such as the IUCN Red List criteria, should be used to assess reintroduction success. [13] Successful reintroduction programs should yield viable and self-sustainable populations in the long-term. The IUCN/SSC Re-introduction Specialist Group & Environment Agency, in their 2011 Global Re-introduction Perspectives, compiled reintroduction case studies from around the world. [14] 184 case studies were reported on a range of species which included invertebrates, fish, amphibians, reptiles, birds, mammals, and plants. Assessments from all of the studies included goals, success indicators, project summary, major difficulties faced, major lessons learned, and success of project with reasons for success or failure. A similar assessment focused solely on plants found high rates of success for rare species reintroductions. [15] An analysis of data from the Center for Plant Conservation International Reintroduction Registry found that, for the 49 cases where data were available, 92% of the reintroduced plant populations survived two years. The Siberian tiger population has rebounded from 40 individuals in the 1940s to around 500 in 2007. The Siberian tiger population is now the largest un-fragmented tiger population in the world. [16] Yet, a high proportion of translocations and reintroductions have not been successful in establishing viable populations. [17] For instance, in China reintroduction of captive Giant Pandas have had mixed effects. The initial pandas released from captivity all died quickly after reintroduction. [18] Even now that they have improved their ability to reintroduce pandas, concern remains over how well the captive-bred pandas will fare with their wild relatives. [19]

Many factors can attribute to the success or failure of a reintroduction. Predators, food, pathogens, competitors, and weather can all affect a reintroduced population's ability to grow, survive, and reproduce. The number of animals reintroduced in an attempt should also vary with factors such as social behavior, expected rates of predation, and density in the wild. [20] Animals raised in captivity may experience stress during captivity or translocation, which can weaken their immune systems. [21] The IUCN reintroduction guidelines emphasize the need for an assessment of the availability of suitable habitat as a key component of reintroduction planning. [22] Poor assessment of the release site can increase the chances that the species will reject the site and perhaps move to a less suitable environment. This can decrease the species fitness and thus decrease chances for survival. [21] They state that restoration of the original habitat and amelioration of causes of extinction must be explored and considered as essential conditions for these projects. Unfortunately, the monitoring period that should follow reintroductions often remains neglected. [23]

When a species has been extirpated from a site where it previously existed, individuals that will comprise the reintroduced population must be sourced from wild or captive populations. When sourcing individuals for reintroduction, it is important to consider local adaptation, adaptation to captivity (for ex situ conservation), the possibility of inbreeding depression and outbreeding depression, and taxonomy, ecology, and genetic diversity of the source population. [2] Reintroduced populations experience increased vulnerability to influences of drift, selection, and gene flow evolutionary processes due to their small sizes, climatic and ecological differences between source and native habitats, and presence of other mating-compatible populations. [11] [24] [25] [26]

If the species slated for reintroduction is rare in the wild, it is likely to have unusually low population numbers, and care should be taken to avoid inbreeding and inbreeding depression. [2] Inbreeding can change the frequency of allele distribution in a population, and potentially result in a change to crucial genetic diversity. [2] Additionally, outbreeding depression can occur if a reintroduced population can hybridize with existing populations in the wild, which can result in offspring with reduced fitness, and less adaptation to local conditions. To minimize both, practitioners should source for individuals in a way that captures as much genetic diversity as possible, and attempt to match source site conditions to local site conditions as much as possible. [2]

Capturing as much genetic diversity as possible, measured as heterozygosity, is suggested in species reintroductions. [2] Some protocols suggest sourcing approximately 30 individuals from a population will capture 95% of the genetic diversity. [2] Maintaining genetic diversity in the recipient population is crucial to avoiding the loss of essential local adaptations, minimizing inbreeding depression, and maximizing fitness of the reintroduced population.

Ecological similarity Edit

Plants or animals that undergo reintroduction may exhibit reduced fitness if they are not sufficiently adapted to local environmental conditions. Therefore, researchers should consider ecological and environmental similarity of source and recipient sites when selecting populations for reintroduction. Environmental factors to consider include climate and soil traits (pH, percent clay, silt and sand, percent combustion carbon, percent combustion nitrogen, concentration of Ca, Na, Mg, P, K). [6] Historically, sourcing plant material for reintroductions has followed the rule "local is best," as the best way to preserve local adaptations, with individuals for reintroductions selected from the most geographically proximate population. [27] However, geographic distance was shown in a common garden experiment to be an insufficient predictor of fitness. [6] Additionally, projected climatic shifts induced by climate change have led to the development of new seed sourcing protocols that aim to source seeds that are best adapted to project climate conditions. [28] Conservation agencies have developed seed transfer zones that serve as guidelines for how far plant material can be transported before it will perform poorly. [29] Seed transfer zones take into account proximity, ecological conditions, and climatic conditions in order to predict how plant performance will vary from one zone to the next. A study of the reintroduction of Castilleja levisecta found that the source populations most physically near the reintroduction site performed the poorest in a field experiment, while those from the source population whose ecological conditions most closely matched the reintroduction site performed best, demonstrating the importance of matching the evolved adaptations of a population to the conditions at the reintroduction site. [30]

Adaptation to captivity Edit

Some reintroduction programs use plants or animals from captive populations to form a reintroduced population. [2] When reintroducing individuals from a captive population to the wild, there is a risk that they have adapted to captivity due to differential selection of genotypes in captivity versus the wild. The genetic basis of this adaptation is selection of rare, recessive alleles that are deleterious in the wild but preferred in captivity. [11] Consequently, animals adapted to captivity show reduced stress tolerance, increased tameness, and loss of local adaptations. [31] Plants also can show adaptations to captivity through changes in drought tolerance, nutrient requirements, and seed dormancy requirements. [32] Extent of adaptation is directly related to intensity of selection, genetic diversity, effective population size and number of generations in captivity. Characteristics selected for in captivity are overwhelmingly disadvantageous in the wild, so such adaptations can lead to reduced fitness following reintroduction. Reintroduction projects that introduce wild animals generally experience higher success rates than those that use captive-bred animals. [11] Genetic adaptation to captivity can be minimized through management methods: by maximizing generation length and number of new individuals added to the captive population minimizing effective population size, number of generations spent in captivity, and selection pressure and reducing genetic diversity by fragmenting the population. [2] [11] For plants, minimizing adaptation to captivity is usually achieved by sourcing plant material from a seed bank, where individuals are preserved as wild-collected seeds, and have not had the chance to adapt to conditions in captivity. However, this method is only plausible for plants with seed dormancy. [11]

Genetic trade-offs Edit

In reintroductions from captivity, translocation of animals from captivity to the wild has implications for both captive and wild populations. Reintroduction of genetically valuable animals from captivity improves genetic diversity of reintroduced populations while depleting captive populations conversely, genetically valuable captive-bred animals may be closely related to individuals in the wild and thus increase risk of inbreeding depression if reintroduced. Increasing genetic diversity is favored with removal of genetically overrepresented individuals from captive populations and addition of animals with low genetic relatedness to the wild. [33] [34] However in practice, initial reintroduction of individuals with low genetic value to the captive population is recommended to allow for genetic assessment before translocation of valuable individuals. [34]

A cooperative approach to reintroduction by ecologists and biologists could improve research techniques. For both preparation and monitoring of reintroductions, increasing contacts between academic population biologists and wildlife managers is encouraged within the Survival Species Commission and the IUCN. The IUCN states that a re-introduction requires a multidisciplinary approach involving a team of persons drawn from a variety of backgrounds. [22] A survey by Wolf et al. in 1998 indicated that 64% of reintroduction projects have used subjective opinion to assess habitat quality. [21] This means that most reintroduction evaluation has been based on human anecdotal evidence and not enough has been based on statistical findings. Seddon et al. (2007) suggest that researchers contemplating future reintroductions should specify goals, overall ecological purpose, and inherent technical and biological limitations of a given reintroduction, and planning and evaluation processes should incorporate both experimental and modeling approaches. [3]

Monitoring the health of individuals, as well as the survival, is important both before and after the reintroduction. Intervention may be necessary if the situation proves unfavorable. [22] Population dynamics models that integrate demographic parameters and behavioral data recorded in the field can lead to simulations and tests of a priori hypotheses. Using previous results to design further decisions and experiments is a central concept of adaptive management. In other words, learning by doing can help in future projects. Population ecologists should therefore collaborate with biologists, ecologists, and wildlife management to improve reintroduction programs. [35]

Genetic monitoring Edit

For reintroduced populations to successfully establish and maximize reproductive fitness, practitioners should perform genetic tests to select which individuals will be the founders of reintroduced populations and to continue monitoring populations post-reintroduction. [4] A number of methods are available to measure the genetic relatedness between and variation among individuals within populations. Common genetic diversity assessment tools include microsatellite markers, mitochondrial DNA analyses, alloenzymes, and amplified fragment length polymorphism markers. [36] Post-reintroduction, genetic monitoring tools can be used to obtain data such as population abundance, effective population size, and population structure, and can also be used to identify instances of inbreeding within reintroduced populations or hybridization with existing populations that are genetically compatible. Long-term genetic monitoring is recommended post-reintroduction to track changes in genetic diversity of the reintroduced population and determine success of a reintroduction program. Adverse genetic changes such as loss of heterozygosity may indicate management intervention, such as population supplementation, is necessary for survival of the reintroduced population. [37] [38] [39]

The RSG is a network of specialists whose aim is to combat the ongoing and massive loss of biodiversity by using re-introductions as a responsible tool for the management and restoration of biodiversity. It does this by actively developing and promoting sound inter-disciplinary scientific information, policy, and practice to establish viable wild populations in their natural habitats. The role of the RSG is to promote the re-establishment of viable populations in the wild of animals and plants. The need for this role was felt due to the increased demand from re-introduction practitioners, the global conservation community and increase in re-introduction projects worldwide.

Increasing numbers of animal and plant species are becoming rare, or even extinct in the wild. In an attempt to re-establish populations, species can – in some instances – be re-introduced into an area, either through translocation from existing wild populations, or by re-introducing captive-bred animals or artificially propagated plants.

Watch the video: APBio Ch 44 Population Ecology, Pt 2: Regulation of Population Size, rK Patterns, Humans (December 2022).