Effective population size

From Wikipedia, the free encyclopedia

The effective population size is "the number of individuals in a population who contribute offspring to the next generation," or all the breeding adults in that population. Genetically derived estimates of effective population size tend to provide a lower number than an actual head count would provide.^[1] In more technical terms, the effective population size is the number of individuals that an idealised population would need to have, in order for some specified quantity of interest to be the same in the idealised population as in the real population. Idealised populations are based on unrealistic but convenient simplifications such as random mating, simultaneous birth of each new generation, constant population size, and equal numbers of children per parent. In some simple scenarios, the effective population size is the number of breeding individuals in the population. However, for most quantities of interest and most real populations, the census population size N of a real population is usually larger than the effective population size N_e. The same population may have multiple effective population sizes, for different properties of interest, including for different genetic loci.

The effective population size is most commonly measured with respect to the coalescence time. In an idealised diploid population with no selection at any locus, the expectation of the coalescence time in generations is equal to twice the census population size. The effective population size is measured as within-species genetic diversity divided by four times the mutation rate, because in such an idealised population, the heterozygosity is equal to ${\displaystyle 4N\mu }$. In a population with selection at many loci and abundant linkage disequilibrium, the coalescent effective population size may not reflect the census population size at all, or may reflect its logarithm.

The concept of effective population size was introduced in the field of population genetics in 1931 by the American geneticist Sewall Wright.^[2][3]

Overview: Types of effective population size

Depending on the quantity of interest, effective population size can be defined in several ways. Ronald Fisher and Sewall Wright originally defined it as "the number of breeding individuals in an idealised population that would show the same amount of dispersion of allele frequencies under random genetic drift or the same amount of inbreeding as the population under consideration". More generally, an effective population size may be defined as the number of individuals in an idealised population that has a value of any given population genetic quantity that is equal to the value of that quantity in the population of interest. The two population genetic quantities identified by Wright were the one-generation increase in variance across replicate populations (variance effective population size) and the one-generation change in the inbreeding coefficient (inbreeding effective population size). These two are closely linked, and derived from F-statistics, but they are not identical.^[4]

Today, the effective population size is usually estimated empirically with respect to the sojourn or coalescence time, estimated as the within-species genetic diversity divided by the mutation rate, yielding a coalescent effective population size.^[5] Another important effective population size is the selection effective population size 1/s_critical, where s_critical is the critical value of the selection coefficient at which selection becomes more important than genetic drift.^[6]

Empirical measurements

In Drosophila populations of census size 16, the variance effective population size has been measured as equal to 11.5.^[7] This measurement was achieved through studying changes in the frequency of a neutral allele from one generation to another in over 100 replicate populations.

For coalescent effective population sizes, a survey of publications on 102 mostly wildlife animal and plant species yielded 192 N_e/N ratios. Seven different estimation methods were used in the surveyed studies. Accordingly, the ratios ranged widely from 10^-6 for Pacific oysters to 0.994 for humans, with an average of 0.34 across the examined species.^[8] A genealogical analysis of human hunter-gatherers (Eskimos) determined the effective-to-census population size ratio for haploid (mitochondrial DNA, Y chromosomal DNA), and diploid (autosomal DNA) loci separately: the ratio of the effective to the census population size was estimated as 0.6–0.7 for autosomal and X-chromosomal DNA, 0.7–0.9 for mitochondrial DNA and 0.5 for Y-chromosomal DNA.^[9]

Variance effective size

References missing In the Wright-Fisher idealized population model, the conditional variance of the allele frequency ${\displaystyle p'}$, given the allele frequency ${\displaystyle p}$ in the previous generation, is

${\displaystyle \operatorname {var} (p'\mid p)={p(1-p) \over 2N}.}$

Let ${\displaystyle {\widehat {\operatorname {var} }}(p'\mid p)}$ denote the same, typically larger, variance in the actual population under consideration. The variance effective population size ${\displaystyle N_{e}^{(v)}}$ is defined as the size of an idealized population with the same variance. This is found by substituting ${\displaystyle {\widehat {\operatorname {var} }}(p'\mid p)}$ for ${\displaystyle \operatorname {var} (p'\mid p)}$ and solving for ${\displaystyle N}$ which gives

${\displaystyle N_{e}^{(v)}={p(1-p) \over 2{\widehat {\operatorname {var} }}(p)}.}$

Theoretical examples

In the following examples, one or more of the assumptions of a strictly idealised population are relaxed, while other assumptions are retained. The variance effective population size of the more relaxed population model is then calculated with respect to the strict model.

Variations in population size

Population size varies over time. Suppose there are t non-overlapping generations, then effective population size is given by the harmonic mean of the population sizes^[10]:

${\displaystyle {1 \over N_{e}}={1 \over t}\sum _{i=1}^{t}{1 \over N_{i}}}$

For example, say the population size was N = 10, 100, 50, 80, 20, 500 for six generations (t = 6). Then the effective population size is the harmonic mean of these, giving:

${\displaystyle {1 \over N_{e}}}$	${\displaystyle ={{\begin{matrix}{\frac {1}{10}}\end{matrix}}+{\begin{matrix}{\frac {1}{100}}\end{matrix}}+{\begin{matrix}{\frac {1}{50}}\end{matrix}}+{\begin{matrix}{\frac {1}{80}}\end{matrix}}+{\begin{matrix}{\frac {1}{20}}\end{matrix}}+{\begin{matrix}{\frac {1}{500}}\end{matrix}} \over 6}}$
	${\displaystyle ={0.1945 \over 6}}$
	${\displaystyle =0.032416667}$
${\displaystyle N_{e}}$	${\displaystyle =30.8}$

Note this is less than the arithmetic mean of the population size, which in this example is 126.7. The harmonic mean tends to be dominated by the smallest bottleneck that the population goes through.

Dioeciousness

If a population is dioecious, i.e. there is no self-fertilisation then

${\displaystyle N_{e}=N+{\begin{matrix}{\frac {1}{2}}\end{matrix}}}$

or more generally,

${\displaystyle N_{e}=N+{\begin{matrix}{\frac {D}{2}}\end{matrix}}}$

where D represents dioeciousness and may take the value 0 (for not dioecious) or 1 for dioecious.

When N is large, N_e approximately equals N, so this is usually trivial and often ignored:

${\displaystyle N_{e}=N+{\begin{matrix}{\frac {1}{2}}\approx N\end{matrix}}}$

Variance in reproductive success

If population size is to remain constant, each individual must contribute on average two gametes to the next generation. An idealized population assumes that this follows a Poisson distribution so that the variance of the number of gametes contributed, k is equal to the mean number contributed, i.e. 2:

${\displaystyle \operatorname {var} (k)={\bar {k}}=2.}$

However, in natural populations the variance is often larger than this. The vast majority of individuals may have no offspring, and the next generation stems only from a small number of individuals, so

${\displaystyle \operatorname {var} (k)>2.}$

The effective population size is then smaller, and given by:

${\displaystyle N_{e}^{(v)}={4N-2D \over 2+\operatorname {var} (k)}}$

Note that if the variance of k is less than 2, N_e is greater than N. In the extreme case of a population experiencing no variation in family size, in a laboratory population in which the number of offspring is artificially controlled, V_k = 0 and N_e = 2N.

Non-Fisherian sex-ratios

When the sex ratio of a population varies from the Fisherian 1:1 ratio, effective population size is given by:

${\displaystyle N_{e}^{(v)}=N_{e}^{(F)}={4N_{m}N_{f} \over N_{m}+N_{f}}}$

Where N_m is the number of males and N_f the number of females. For example, with 80 males and 20 females (an absolute population size of 100):

${\displaystyle N_{e}}$	${\displaystyle ={4\times 80\times 20 \over 80+20}}$
	${\displaystyle ={6400 \over 100}}$
	${\displaystyle =64}$

Again, this results in N_e being less than N.

Inbreeding effective size

Alternatively, the effective population size may be defined by noting how the average inbreeding coefficient changes from one generation to the next, and then defining N_e as the size of the idealized population that has the same change in average inbreeding coefficient as the population under consideration. The presentation follows Kempthorne (1957).^[11]

For the idealized population, the inbreeding coefficients follow the recurrence equation

${\displaystyle F_{t}={\frac {1}{N}}\left({\frac {1+F_{t-2}}{2}}\right)+\left(1-{\frac {1}{N}}\right)F_{t-1}.}$

Using Panmictic Index (1 − F) instead of inbreeding coefficient, we get the approximate recurrence equation

${\displaystyle 1-F_{t}=P_{t}=P_{0}\left(1-{\frac {1}{2N}}\right)^{t}.}$

The difference per generation is

${\displaystyle {\frac {P_{t+1}}{P_{t}}}=1-{\frac {1}{2N}}.}$

The inbreeding effective size can be found by solving

${\displaystyle {\frac {P_{t+1}}{P_{t}}}=1-{\frac {1}{2N_{e}^{(F)}}}.}$

This is

${\displaystyle N_{e}^{(F)}={\frac {1}{2\left(1-{\frac {P_{t+1}}{P_{t}}}\right)}}}$

although researchers rarely use this equation directly.

Theoretical example: overlapping generations and age-structured populations

When organisms live longer than one breeding season, effective population sizes have to take into account the life tables for the species.

Haploid

Assume a haploid population with discrete age structure. An example might be an organism that can survive several discrete breeding seasons. Further, define the following age structure characteristics:

${\displaystyle v_{i}=}$ Fisher's reproductive value for age ${\displaystyle i}$,

${\displaystyle \ell _{i}=}$ The chance an individual will survive to age ${\displaystyle i}$, and

${\displaystyle N_{0}=}$ The number of newborn individuals per breeding season.

The generation time is calculated as

${\displaystyle T=\sum _{i=0}^{\infty }\ell _{i}v_{i}=}$ average age of a reproducing individual

Then, the inbreeding effective population size is^[12]

${\displaystyle N_{e}^{(F)}={\frac {N_{0}T}{1+\sum _{i}\ell _{i+1}^{2}v_{i+1}^{2}({\frac {1}{\ell _{i+1}}}-{\frac {1}{\ell _{i}}})}}.}$

Diploid

Similarly, the inbreeding effective number can be calculated for a diploid population with discrete age structure. This was first given by Johnson,^[13] but the notation more closely resembles Emigh and Pollak.^[14]

Assume the same basic parameters for the life table as given for the haploid case, but distinguishing between male and female, such as N₀^ƒ and N₀^m for the number of newborn females and males, respectively (notice lower case ƒ for females, compared to upper case F for inbreeding).

The inbreeding effective number is

${\displaystyle {\begin{aligned}{\frac {1}{N_{e}^{(F)}}}={\frac {1}{4T}}\left\{{\frac {1}{N_{0}^{f}}}+{\frac {1}{N_{0}^{m}}}+\sum _{i}\left(\ell _{i+1}^{f}\right)^{2}\left(v_{i+1}^{f}\right)^{2}\left({\frac {1}{\ell _{i+1}^{f}}}-{\frac {1}{\ell _{i}^{f}}}\right)\right.\,\,\,\,\,\,\,\,&\\\left.{}+\sum _{i}\left(\ell _{i+1}^{m}\right)^{2}\left(v_{i+1}^{m}\right)^{2}\left({\frac {1}{\ell _{i+1}^{m}}}-{\frac {1}{\ell _{i}^{m}}}\right)\right\}.&\end{aligned}}}$

  

 

Coalescent effective size

According to the neutral theory of molecular evolution, a neutral allele remains in a population for Ne generations, where Ne is the effective population size. An idealised diploid population will have a pairwise nucleotide diversity equal to 4${\displaystyle \mu }$Ne, where ${\displaystyle \mu }$ is the mutation rate. The sojourn effective population size can therefore be estimated empirically by dividing the nucleotide diversity by the mutation rate.^[5]

The coalescent effective size may have little relationship to the number of individuals physically present in a population.^[15] Measured coalescent effective population sizes vary between genes in the same population, being low in genome areas of low recombination and high in genome areas of high recombination.^[16][17] Sojourn times are proportional to N in neutral theory, but for alleles under selection, sojourn times are proportional to log(N). Genetic hitchhiking can cause neutral mutations to have sojourn times proportional to log(N): this may explain the relationship between measured effective population size and the local recombination rate.

Selection effective size

In an idealised Wright-Fisher model, the fate of an allele, beginning at an intermediate frequency, is largely determined by selection if the selection coefficient s ≫ 1/N, and largely determined by neutral genetic drift if s ≪ 1/N. In real populations, the cutoff value of s may depend instead on local recombination rates.^[6][18] This limit to selection in a real population may be captured in a toy Wright-Fisher simulation through the appropriate choice of Ne. Populations with different selection effective population sizes are predicted to evolve profoundly different genome architectures.^[19][20]

Restoration ecology

From Wikipedia, the free encyclopedia

 

Recently constructed wetland regeneration in Australia, on a site previously used for agriculture

 

Rehabilitation of a portion of Johnson Creek, to restore bioswale and flood control functions of the land which had long been converted to pasture for cow grazing. The horizontal logs can float, but are anchored by the posts. Just-planted trees will eventually stabilize the soil. The fallen trees with roots jutting into the stream are intended to enhance wildlife habitat. The meandering of the stream is enhanced here by a factor of about three times, perhaps to its original course.

Restoration ecology emerged as a separate field in ecology in the late twentieth century. It is the scientific study supporting the practice of ecological restoration, which is the practice of renewing and restoring degraded, damaged, or destroyed ecosystems and habitats in the environment by active human intervention and action. Restoration ecology is the academic study of the process, whereas ecological restoration is the actual project or process by restoration practitioners.

Definition

The Society for Ecological Restoration defines "ecological restoration" as an "intentional activity that initiates or accelerates the recovery of an ecosystem with respect to its health, integrity and sustainability".^[1] Ecological restoration includes a wide scope of projects including erosion control, reforestation, removal of non-native species and weeds, revegetation of disturbed areas,daylighting streams, reintroduction of native species (preferably native species that have local adaptation), and habitat and range improvement for targeted species.

E. O. Wilson, a biologist, states, "Here is the means to end the great extinction spasm. The next century will, I believe, be the era of restoration in ecology."^[2]

History

Indigenous peoples, land managers, stewards, and laypeople have been practicing ecological restoration or ecological management for hundreds, if not thousands, of years.^[3] However, the scientific field of "restoration ecology" was not first formally identified and coined until the late twentieth century, by John Aber and William Jordan III when they were at the University of Wisconsin-Madison.^[4] In the late twentieth century, environmental disasters caused by industry were taking place motivating people toward restoration. They held the first international meetings on this topic in Madison, Wisconsin during which attendees visited the University of Wisconsin-Madison Arboretum—the oldest restoration ecology project made famous by Professor Aldo Leopold.^[5] The study of restoration ecology has since become a robust and independent scientific discipline and the commercial applications of ecological restoration have tremendously increased in recent years.^[6]

Basis for restoration ecology

There is consensus in the scientific community that the current environmental degradation and destruction of many of the Earth's biota is considerable and is taking place on a "catastrophically short timescale".^[7] Scientists estimate that the current species extinction rate, or the rate of the Holocene extinction, is 1,000 to 10,000 times higher than the normal, background rate.^[8][9][10]

Many people believe that biodiversity has intrinsic value and that humans have a responsibility to conserve biodiversity, and an obligation to future generations to preserve nature.^[11] Natural ecosystems are also known to provide ecosystem services in the form of resources such as food, fuel, and timber; the purification of air and water; the detoxification and decomposition of wastes; the regulation of climate; the regeneration of soil fertility; and the pollination of crops. Such processes have been estimated to be worth trillions of dollars annually.^[12][11]

Habitat loss is the leading cause of both species extinctions^[10] and ecosystem service decline.^[12] Two methods to slow the rate of species extinction and ecosystem service decline are the conservation of currently viable habitat, and the restoration of degraded habitat.

Theoretical foundations

Restoration ecology draws on a wide range of ecological concepts.

Disturbance

Disturbance is a change in environmental conditions that disrupts the functioning of an ecosystem. Disturbance, at a variety of spatial and temporal scales, is a natural component of many communities.^[13] For example, many forest and grassland restorations implement fire as a natural disturbance regime.

Humans previously had a limited impact on ecosystems, but the severity and scope of human impact has grown in the last few centuries. It important to understand and minimize anthropogenic impacts on ecosystems. It is also important to differentiate between human-caused and naturally-occurring disturbances.

Succession

Ecological succession is the process by which the species within a community change over time. Following a disturbance, an ecosystem generally progresses from a simple level of organization (i.e. few dominant pioneer species) to a more complex community (i.e. many interdependent species) over time. Depending on the severity of the disturbance, restoration often consists of initiating, assisting, or accelerating ecological successional processes.^[14]

In many ecosystems, communities tend to recover following mild to moderate natural and anthropogenic disturbances. Restoration in these systems involves hastening natural successional trajectories. However, a system that has experienced a more severe disturbance (i.e. physical or chemical alteration of the environment) may require intensive restorative efforts to recreate environmental conditions that favor natural successional processes. This ability to recover is called resilience.

Fragmentation

Habitat fragmentation is the emergence of spatial discontinuities in a biological system. Through land use changes (e.g. agriculture) and natural disturbance, ecosystems are broken up into smaller parts. Small fragments of habitat can support only small populations and small populations are more vulnerable to extinction. Furthermore, fragmenting ecosystems decreases interior habitat. Habitat along the edge of a fragment has a different range of environmental conditions and therefore supports different species than the interior. Fragmentation effectively reduces interior habitat and may lead to the extinction of those species which require interior habitat. Restorative projects can increase the effective size of a habitat by simply adding area or by planting habitat corridors that link and fill in the gap between two isolated fragments. Reversing the effects of fragmentation and increasing habitat connectivity can be an important effect of restoration ecology.^[15]

Ecosystem function

Ecosystem function describes the foundational processes of natural systems, including nutrient cycles and energy fluxes. These processes are the most basic and essential components of ecosystems. An understanding of the full complexity and intricacies of these cycles is necessary to address any ecological processes that may be degraded. A functional ecosystem, that is completely self-perpetuating and does not require management, is the ultimate goal of restorative efforts. Ecosystem functions are emergent properties of the system as a whole, thus monitoring and management are crucial for the long-term stability of ecosystems.^{[citation needed]}

Community assembly

Community assembly "is a framework that can unify virtually all of (community) ecology under a single conceptual umbrella".^[16] Community assembly theory attempts to explain the existence of environmentally similar sites with differing assemblages of species. It assumes that species have similar niche requirements, so that community formation is a product of random fluctuations from a common species pool.^[17] Essentially, if all species are fairly ecologically equivalent, then random variation in colonization, and migration and extinction rates between species, drive differences in species composition between sites with comparable environmental conditions.^{[citation needed]}

Population genetics

Restoration ecology, and the practice of ecological restoration, must consider population genetic processes in order to ensure that restored populations maintain genetic diversity conducive to population establishment and reproduction. Population genetic processes that can alter restored population genetics include founder effects, inbreeding depression, outbreeding depression, genetic drift, gene flow, and more. Such processes can predict whether or not a species successfully establishes at a restoration site.^[18][19]

Applications

Soil heterogeneity effects on community heterogeneity

Spatial heterogeneity of resources can influence plant community composition, diversity, and assembly trajectory. Baer et al. (2005) manipulated soil resource heterogeneity in a tallgrass prairie restoration project. They found increasing resource heterogeneity, which on its own was insufficient to insure species diversity in situations where one species may dominate across the range of resource levels. Their findings were consistent with the theory regarding the role of ecological filters on community assembly. The establishment of a single species, best adapted to the physical and biological conditions can play an inordinately important role in determining the community structure.^[20]

Invasion and restoration

Restoration is used as a tool for reducing the spread of invasive plant species in a number of ways. The first method views restoration primarily as a means to reduce the presence of invasive species and limit their spread. As this approach emphasizes control of invaders, the restoration techniques can differ from typical restoration projects.^[21][22] The goal of such projects is not necessarily to restore an entire ecosystem or habitat.^[23] These projects frequently use lower diversity mixes of aggressive native species seeded at high density. These projects frequently use lower diversity mixes of aggressive native species seeded at high density.^[24] They are not always actively managed following seeding.^[25] The target areas for this type of restoration are those which are heavily dominated by invasive species. The goals are to first remove the species and then in so doing, reduce the number of invasive seeds being spread to surrounding areas. This approach has been shown to be effective in reducing weeds, although it is not always a sustainable solution long term without additional weed control, such as mowing, or re-seeding.^{[22][25][26][27]}

Restoration projects are also used as a way to better understand what makes an ecological community resistant to invasion. As restoration projects have a broad range of implementation strategies and methods used to control invasive, they can be used by ecologists to test theories about invasion.^[25] Restoration projects have been used to understand how the diversity of the species introduced in the restoration affects invasion. We know that generally higher diversity prairies have lower levels of invasion.^[28] Incorporation of functional ecology has shown that more functionally diverse restorations have lower levels of invasion.^[29] Furthermore, studies have shown that using native species functionally similar to invasive species are better able to compete with invasive species.^[30][31] Restoration ecologists have also used the variety of strategies employed at different restoration sites to better understand the most successful management techniques to control invasion.^[32]

Successional trajectories

Progress along a desired successional pathway may be difficult if multiple stable states exist. Looking over 40 years of wetland restoration data, Klötzli and Gootjans (2001) argue that unexpected and undesired vegetation assemblies "may indicate that environmental conditions are not suitable for target communities".^[33] Succession may move in unpredicted directions, but constricting environmental conditions within a narrow range may rein in the possible successional trajectories and increase the likelihood of a desired outcome.

Application to ecological restoration

Ecosystem restoration for the superb parrot on an abandoned railway line in Australia

 

Forest restoration in action at the Buffelsdraai Landfill Site Community Reforestation Project in South Africa

Sources for restoration

During seed based restoration projects, it is generally recommended to source from local populations, to minimize the effects of maladaptation.^[34] One of the many challenges of restoration is that every species is different and requires different sourcing guidelines. Rather than putting strict distance recommendations, other guidelines recommend sourcing seeds to match similar environmental conditions. For example, sourcing for Castilleja levisecta found that farther source populations that matched similar environmental variables were better suited for the restoration project than closer source populations.^[35] Restoration guidelines vary drastically between states and agency. For example, Minnesota is broken up into 9 seed sourcing zones,^[36] where its neighbor Iowa, is broken into three latitudinal zones.^[37] US Forest Service recently developed provisional seed zones based on a combination of minimum winter temperature zones, aridity, and the Level III ecoregions.^[38]

Rationale

There are many reasons to restore ecosystems. Some include:

• Restoring natural capital such as drinkable water or wildlife populations
• Mitigating climate change (e.g. through carbon sequestration)
• Helping threatened or endangered species^[39]
• Aesthetic reasons ^[40]
• Moral reasons: Human intervention has unnaturally destroyed many habitats, and there exists an innate obligation to restore these destroyed habitats

There exists considerable differences of opinion in how to set restoration goals and how to define their success among conservation groups. Some urge active restoration (e.g. eradicating invasive animals to allow the native ones to survive) and others who believe that protected areas should have the bare minimum of human interference, such as rewilding. Ecosystem restoration has generated controversy. Skeptics doubt that the benefits justify the economic investment or who point to failed restoration projects and question the feasibility of restoration altogether. It can be difficult to set restoration goals, in part because, as Anthony Bradshaw claims, "ecosystems are not static, but in a state of dynamic equilibrium…. [with restoration] we aim [for a] moving target."

Some conservations argue, that though an ecosystem may not be returned to its original state, the functions of the ecosystem (especially ones that provide services to us) may be more valuable than its current configuration (Bradshaw 1987). One reason to consider ecosystem restoration is to mitigate climate change through activities such as afforestation. Afforestation involves replanting forests, which remove carbon dioxide from the air. Carbon dioxide is a leading cause of global warming (Speth, 2005) and capturing it would help alleviate climate change. Another example of a common driver of restoration projects in the United States is the legal framework of the Clean Water Act, which often requires mitigation for damage inflicted on aquatic systems by development or other activities.^{[citation needed]}

Challenges in restoration

Some view ecosystem restoration as impractical, partially because restorations often fall short of their goals. Hilderbrand et al. point out that many times uncertainty (about ecosystem functions, species relationships, and such) is not addressed, and that the time-scales set out for 'complete' restoration are unreasonably short, while other critical markers for full scale restoration are either ignored or abridged due to feasibility concerns.^[41] In other instances an ecosystem may be so degraded that abandonment (allowing a severely degraded ecosystem to recover on its own) may be the wisest option.^[42] Local communities sometimes object to restorations that include the introduction of large predators or plants that require disturbance regimes such as regular fires, citing threat to human habitation in the area (MacDonald et al. 2002). High economic costs can also be perceived as a negative impact of the restoration process.

Public opinion is very important in the feasibility of a restoration; if the public believes that the costs of restoration outweigh the benefits they will not support it (MacDonald et al. 2002).

Many failures have occurred in past restoration projects, many times because clear goals were not set out as the aim of the restoration, or an incomplete understanding of the underlying ecological framework lead to insufficient measures. This may be because, as Peter Alpert says, "people may not [always] know how to manage natural systems effectively".^[43] Furthermore, many assumptions are made about myths of restoration such as carbon copy, where a restoration plan, which worked in one area, is applied to another with the same results expected, but not realized (Hilderbrand et al. 2005).

Contrasting restoration ecology and conservation biology

Restoration ecology may be viewed as a sub-discipline of conservation biology, the scientific study of how to protect and restore biodiversity. Ecological restoration is then a part of the resulting conservation movement.

Both restoration ecologists and conservation biologists agree that protecting and restoring habitat is important for protecting biodiversity. However, conservation biology is primarily rooted in population biology. Because of that, it is generally organized at the population genetic level and assesses specific species populations (i.e. endangered species). Restoration ecology is organized at the community level, which focuses on broader groups within ecosystems.^[44]

In addition, conservation biology often concentrates on vertebrate animals because of their salience and popularity, whereas restoration ecology concentrates on plants. Restoration ecology focuses on plants because restoration projects typically begin by establishing plant communities. Ecological restoration, despite being focused on plants, may also have "poster species" for individual ecosystems and restoration projects.^[44] For example, the Monarch butterfly is a poster species for conserving and restoring milkweed plant habitat, because Monarch butterflies require milkweed plants to reproduce. Finally, restoration ecology has a stronger focus on soils, soil structure, fungi, and microorganisms because soils provide the foundation of functional terrestrial ecosystems.^[45][46]

Science-practice gap

One of the struggles for both fields is a divide between restoration ecology and ecological restoration in practice. Currently, many restoration practitioners as well as scientists feel that science is not being adequately incorporated into ecological restoration projects.^{[47][48][49][50]} In a 2009 survey of practitioners and scientists, the "science-practice gap" was listed as the second most commonly cited reason limiting the growth of both science and practice of restoration.

There are a variety of theories about the cause of this gap. However, it has been well established that one of the main issues is that the questions studied by restoration ecologists are frequently not found useful or easily applicable by land managers.^[47][51] For instance, many publications in restoration ecology characterize the scope of a problem in depth, without providing concrete solutions.^[51] Additionally many restoration ecology studies are carried out under controlled conditions and frequently at scales much smaller than actual restorations.^[25] Whether or not these patterns hold true in an applied context is often unknown. There is evidence that these small scale experiments inflate type II error rates and differ from ecological patterns in actual restorations.^[52][53]

There is further complication in that restoration ecologists who want to collect large scale data on restoration projects can face enormous hurdles in obtaining the data. Managers vary in how much data they collect, and how many records they keep. Some agencies keep only a handful of physical copies of data that make it difficult for the researcher to access.^[54] Many restoration projects are limited by time and money, so data collection and record keeping are not always feasible.^[48] However, this limits the ability of scientists to analyze restoration projects and give recommendations based on empirical data.

Natural Capital Committee's recommendation for a 25-year plan

The UK Natural Capital Committee (NCC) made a recommendation in its second State of Natural Capital report published in March 2014 that in order to meet the Government's goal of being the first generation to leave the environment in a better state than it was inherited, a long-term 25-year plan was needed to maintain and improve England's natural capital. The UK Government has not yet responded to this recommendation.

The Secretary of State for the UK's Department for Environment, Food and Rural Affairs, Owen Paterson, described his ambition for the natural environment and how the work of the Committee fits into this at an NCC event in November 2012: "I do not, however, just want to maintain our natural assets; I want to improve them. I want us to derive the greatest possible benefit from them, while ensuring that they are available for generations to come. This is what the NCC's innovative work is geared towards".^{[citation needed]}