Content deleted Content added
Tom.Reding (talk | contribs) m Category:CS1 errors: deprecated parameters (last-author-amp=y/yes → name-list-style=amp; etc.) |
|||
| (20 intermediate revisions by 13 users not shown) | |||
Line 1:
[[File:Moofushi Kandu fish.jpg|thumb|300px|right|Predator [[bluefin trevally]] sizing up [[Shoaling and schooling|schooling]] [[anchovy|anchovies]], in the [[Maldives]]]]
A [[fishery]] is an area with an associated [[fish]] or [[Aquatic animal|aquatic]] population which is harvested for its [[Commercial fishing|commercial]] or [[Recreational fishing|recreational]] value. Fisheries can be [[Wild fisheries of the world|wild]] or [[Fish farm|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 science|fisheries scientist]]s to determine [[Sustainable yield in fisheries|sustainable yields]].<ref>{{cite journal |
The basic accounting relation for population dynamics is the [[Matrix population models|BIDE]] (Birth, Immigration, Death, Emigration) model, shown as:<ref>{{cite book |last=Caswell |first=H. |year=2001 |title=Matrix population models: Construction, analysis and interpretation |edition=2nd |publisher=Sinauer Associates |location=Sunderland, Massachusetts |isbn=0-87893-096-5 }}</ref>
Line 16:
If these rates are measured over different time intervals, the '''harvestable surplus''' of a fishery can be determined. The harvestable surplus is the number of individuals that can be harvested from the population without affecting long term stability (average population size). The harvest within the harvestable surplus is called '''compensatory mortality''', where the harvest deaths are substituting for the deaths that would otherwise occur naturally. Harvest beyond that is '''additive mortality''', harvest in addition to all the animals that would have died naturally.
Care is needed when applying population dynamics to real world fisheries. Over-simplistic modelling of fisheries has resulted in the collapse of key [[Fish
==History==
The first principle of population dynamics is widely regarded as the exponential law of [[Malthus]], as modelled by the [[Malthusian growth model]]. The early period was dominated by [[demography|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. A more general model formulation was proposed by F.J. Richards in 1959, by which the models of Gompertz, Verhulst and also [[Ludwig von Bertalanffy]] are covered as special cases of the general formulation.<ref>{{cite journal |last=Richards |first=F. J. |year=1959 |title=A Flexible Growth Function for Empirical Use |journal=Journal of Experimental Botany |volume=10 |issue=2 |pages=
==Population size==
Line 36:
==Minimum viable population==
{{Main|Minimum viable population}}
The minimum viable population (MVP) is a lower bound on the population of a species, such that it can survive in the wild. More specifically MVP is the smallest possible size at which a biological population can exist without facing extinction from natural disasters or demographic, environmental, or genetic [[stochastic]]ity.<ref>{{cite web |last=Holsinger |first=Kent |date=2007 |
As a reference standard, MVP is usually given with a population survival probability of somewhere between ninety and ninety-five percent and calculated for between one hundred and one thousand years into the future.
Line 44:
==Maximum sustainable yield==
{{main|Maximum sustainable yield}}
In [[population ecology]] and [[economics]], the [[maximum sustainable yield]] or '''MSY''' is, theoretically, the largest catch that can be taken from a fishery stock over an indefinite period.<ref>{{cite web |author=European Union |date=2006 |url=http://europa.eu/scadplus/leg/en/lvb/l66037.htm |title=Management based on maximum sustainable yield |
This [[logistic function|logistic]] model of growth is produced by a population introduced to a new habitat or with very poor numbers going through a lag phase of slow growth at first. Once it reaches a foothold population it will go through a rapid growth rate that will start to level off once the species approaches carrying capacity. The idea of maximum sustained yield is to decrease population density to the point of highest growth rate possible. This changes the number of the population, but the new number can be maintained indefinitely, ideally.
MSY is extensively used for fisheries management.<ref>{{cite web
</ref><ref>{{cite web |author=New Zealand Ministry of Fisheries |url=http://www.fish.govt.nz/en-nz/SOF/Indicators.htm |title=MSY Harvest Strategies }}</ref> Unlike the logistic (Schaefer) model, MSY in most modern fisheries models occurs at around 30-40% of the unexploited population size.<ref>See e.g. {{cite journal |
However, the approach has been widely criticized as ignoring several key factors involved in fisheries management and has led to the devastating collapse of many fisheries. As a simple calculation, it ignores the size and age of the animal being taken, its reproductive status, and it focuses solely on the species in question, ignoring the damage to the ecosystem caused by the designated level of exploitation and the issue of bycatch. Among [[Conservation biology|conservation biologists]] it is widely regarded as dangerous and misused.<ref name=Epitaph>{{cite journal |last=Larkin |first=P. A. |year=1977 |title=An Epitaph for the Concept of Maximum Sustained Yield |journal=Transactions of the American Fisheries Society |volume=106 |issue=1 |pages=1–11 |doi=10.1577/1548-8659(1977)106<1:AEFTCO>2.0.CO;2 }}</ref><ref name=Lessons>{{cite journal |
==Recruitment==
Line 57:
The recruitment problem is the problem of predicting the number of fish larvae in one season that will survive and become juvenile fish in the next season. It has been called "the central problem of fish population dynamics"<ref>{{cite book |last=Beyer |first=J. E. |year=1981 |title=Aquatic ecosystems-an operational research approach |publisher=University of Washington Press |isbn=0-295-95719-0 }}
</ref> and “the major problem in fisheries science".<ref name="NYT">{{cite news |url=https://www.nytimes.com/2007/03/29/obituaries/29myers.html |title=Ransom A. Myers, 54, Dies; Expert on Loss of Fish Stocks |newspaper=The New York Times |date=29 March 2007 }}</ref> Fish produce huge volumes of larvae, but the volumes are very variable and mortality is high. This makes good predictions difficult.<ref>{{cite
According to [[Daniel Pauly]],<ref name="NYT"/><ref>{{cite
==Fishing effort==
Fishing effort is a measure of the anthropogenic work input used to catch fish. A good measure of the fishing effort will be approximately proportional to the amount of fish captured. Different measures are appropriate for different kinds of fisheries. For example, the fishing effort exerted by a [[fishing fleet]] in a trawl fishery might be measured by summing the products of the engine power for each boat and time it spent at sea (KW × days). For a gill-net fishery the effort might be measured by summing the products of the length of each set net and the time it was set in the water (Km × soak time). In fisheries where boats spend a lot of time looking for fish, a measure based on search time may be used.<ref>{{cite web |url=https://stats.oecd.org/glossary/detail.asp?ID=994OECD |title=Fishing effort |work=Glossary of Statistical Terms |publisher=Review of Fisheries in OECD Countries, 1998 |date=5 March 2003 |
==Overfishing==
Line 69:
The notion of [[overfishing]] hinges on what is meant by an '''acceptable level''' of fishing.
A current operational model used by some fisheries for predicting acceptable levels is the '''Harvest Control Rule''' (HCR). This formalizes and summarizes a management strategy which can actively adapt to subsequent feedback. The HCR is a variable over which the management has some direct control and describes how the harvest is intended to be controlled by management in relation to the state of some indicator of stock status. For example, a harvest control rule can describe the various values of fishing mortality which will be aimed at for various values of the stock abundance. Constant catch and constant fishing mortality are two types of simple harvest control rules.<ref>{{cite web|last1=Coad|first1=Brian W.|last2=McAllister|first2=Don E.|title=Dictionary of Ichthyology|url=http://www.briancoad.com/dictionary/H.htm|
* '''Biological overfishing''' occurs when fishing [[Mortality rate|mortality]] has reached a level where the stock [[biomass]] has negative [[marginalism|marginal growth]] (slowing down biomass growth), as indicated by the red area in the figure. Fish are being taken out of the water so quickly that the replenishment of stock by breeding slows down. If the replenishment continues to slow down for long enough, replenishment will go into reverse and the population will decrease.
Line 76:
==Metapopulation==
{{Main|Metapopulation}}
A metapopulation is a group of spatially separated populations of the same [[species]] which interact at some level. The term was coined by [[Richard Levins]] in 1969. The idea has been most broadly applied to species in naturally or artificially [[habitat fragmentation|fragmented habitats]]. In Levins' own words, it consists of "a population of populations".<ref>{{cite journal |last=Levins |first=R. |year=1969 |title=Some demographic and genetic consequences of environmental heterogeneity for biological control |journal=Bulletin of the Entomological Society of America |volume=15 |issue=3 |pages=
A metapopulation generally consists of several distinct populations together with areas of suitable habitat which are currently unoccupied. Each population cycles in relative independence of the other populations and eventually goes extinct as a consequence of demographic stochasticity (fluctuations in population size due to random demographic events); the smaller the population, the more prone it is to extinction.
Line 104:
;Classic examples
# In [[lake]]s, [[piscivore|piscivorous]] fish can dramatically reduce populations of [[zooplankton|zooplanktivorous]] fish, [[zooplankton|zooplanktivorous]] fish can dramatically alter [[freshwater]] [[zooplankton]] communities, and [[zooplankton]] grazing can in turn have large impacts on [[phytoplankton]] communities. Removal of piscivorous fish can change lake water from clear to green by allowing phytoplankton to flourish.<ref>{{cite journal |
# In the [[Eel River (California)|Eel River]], in Northern [[California]], fish ([[Rainbow trout|steelhead]] and [[California Roach|roach]]) consume fish larvae and predatory [[insects]]. These smaller [[predator]]s prey on [[midge]] larvae, which feed on [[algae]]. Removal of the larger fish increases the abundance of algae.<ref>{{cite journal |last=Power |first=M. E. |year=1990 |title=Effects of fish in river food webs |journal=Science |volume=250 |issue=4982 |pages=
# In [[Pacific Ocean|Pacific]] [[kelp forest]]s, [[sea otters]] feed on [[sea urchin]]s. In areas where sea otters have been [[hunting|hunt]]ed to [[local extinction|extinction]], sea urchins increase in abundance and decimate [[kelp]]<ref>{{cite journal |
A recent theory, the [[mesopredator release hypothesis]], states that the decline of top predators in an ecosystem results in increased populations of medium-sized predators (mesopredators).
==Basic models==
* The classic population equilibrium model is [[Pierre François Verhulst|Verhulst's]] 1838 [[Logistic function#In ecology: modeling population growth|growth model]]: <math display="block"> \frac{dN}{dt} = r N \left(1 - \frac {N}{K} \right)</math> where ''N''(''t'') represents number of individuals at time ''t'', ''r'' the intrinsic growth rate and ''K'' is the [[carrying capacity]], or the maximum number of individuals that the environment can support.
* The individual growth model, published by [[Ludwig von Bertalanffy|von Bertalanffy]] in 1934, can be used to model the rate at which fish grow. It exists in a number of versions, but in its simplest form it is expressed as a [[differential equation]] of length (''L'') over time (''t''): <math display="block">L'(t) = r_B \left( L_\infty - L(t) \right)</math> where ''r''<sub>''B''</sub> is the von Bertalanffy growth rate and ''L''<sub>∞</sub> the ultimate length of the individual.▼
* [[Milner Baily Schaefer|Schaefer]] published a fishery equilibrium model based on the [[Pierre François Verhulst|Verhulst]] model with an assumption of a bi-linear catch equation, often referred to as the Schaefer short-term catch equation: <math display="block">H(E,X)=q E X\!</math> where the variables are; ''H'', referring to catch (harvest) over a given period of time (e.g. a year); ''E'', the fishing effort over the given period; ''X'', the fish stock biomass at the beginning of the period (or the average biomass), and the parameter ''q'' represents the catchability of the stock. {{pb}} Assuming the catch to equal the net natural growth in the population over the same period (<math>\dot{X}=0</math>), the equilibrium catch is a function of the long term fishing effort ''E'': <math display="block">H(E) = q K E \left(1 - \frac{qE}{r}\right)</math> ''r'' and ''K'' being biological parameters representing intrinsic growth rate and natural equilibrium biomass respectively.
* The [[Baranov catch equation]] of 1918 is perhaps the most used equation in fisheries modelling.<ref>{{Cite journal | last = Quinn | first = Terrance J. II| title = Ruminations on the development and future of population dynamics models in fisheries | doi = 10.1111/j.1939-7445.2003.tb00119.x | journal = Natural Resource Modeling | volume = 16 | issue = 4 | pages = 341–392| year = 2003
* The [[Beverton–Holt model]], introduced in the context of fisheries in 1957, is a classic discrete-time population model which gives the [[expected value|expected]] number ''n''<sub> ''t''+1</sub> (or density) of individuals in generation ''t'' + 1 as a function of the number of individuals in the previous generation, <math display="block">n_{t+1} = \frac{R_0 n_t}{1+ n_t/M}. </math> Here ''R''<sub>0</sub> is interpreted as the proliferation rate per generation and ''K'' = (''R''<sub>0</sub> − 1) ''M'' is the [[carrying capacity]] of the environment.▼
▲* The individual growth model, published by [[Ludwig von Bertalanffy|von Bertalanffy]] in 1934, can be used to model the rate at which fish grow. It exists in a number of versions, but in its simplest form it is expressed as a [[differential equation]] of length (''L'') over time (''t''):
▲* The [[Baranov catch equation]] of 1918 is perhaps the most used equation in fisheries modelling.<ref>{{Cite journal | last = Quinn | first = Terrance J. II| title = Ruminations on the development and future of population dynamics models in fisheries | doi = 10.1111/j.1939-7445.2003.tb00119.x | journal = Natural Resource Modeling | volume = 16 | issue = 4 | pages = 341–392| year = 2003| pmid = | pmc = | citeseerx = 10.1.1.473.3765}}</ref> It gives the catch in numbers as a function of initial population abundance ''N''<sub>''0''</sub> and fishing ''F'' and natural mortality ''M'':
▲:Here ''r'' is interpreted as an intrinsic growth rate and ''k'' as the [[carrying capacity]] of the environment. The Ricker model was introduced in the context of the fisheries by [[Bill Ricker|Ricker]] (1954).<ref>Ricker, WE (1954). Stock and recruitment. Journal of the Fisheries Research Board of Canada.</ref>
▲* The [[Beverton–Holt model]], introduced in the context of fisheries in 1957, is a classic discrete-time population model which gives the [[expected value|expected]] number ''n''<sub> ''t''+1</sub> (or density) of individuals in generation ''t'' + 1 as a function of the number of individuals in the previous generation,
==Predator–prey equations==
Line 158 ⟶ 124:
An extension to these are the [[competitive Lotka–Volterra equations]], which provide a simple model of the population dynamics of species competing for some common resource.
In the 1930s [[Alexander John Nicholson|Alexander Nicholson]] and [[Victor Albert Bailey|Victor Bailey]] developed a model to describe the population dynamics of a coupled predator–prey system. The model assumes that predators search for prey at random, and that both predators and prey are assumed to be distributed in a non-contiguous ("clumped") fashion in the environment.<ref name="Hopper">{{cite journal |last=Hopper |first=J. L. |year=1987 |title=Opportunities and Handicaps of Antipodean Scientists: A. J. Nicholson and V. A. Bailey on the Balance of Animal Populations |journal=Historical Records of Australian Science |volume=7 |issue=2 |pages=179–188 |doi=10.1071/HR9880720179 |url=http://www.publish.csiro.au/paper/HR9880720179.htm }}</ref>
In the late 1980s, a credible, simple alternative to the Lotka–Volterra predator-prey model (and its common prey dependent generalizations) emerged, the ratio dependent or [[Arditi–Ginzburg equations|Arditi–Ginzburg model]].<ref>{{cite journal |
==See also==
Line 167 ⟶ 133:
* [[Depensation]]
* [[Huffaker's mite experiment]]
* [[Wild fisheries]]▼
* [[Overfishing]]
* [[Overexploitation]]
* [[Population modeling]]
* [[
* [[Tragedy of the commons]]{{Div col end}}
▲* [[Wild fisheries]]
==References==
Line 179 ⟶ 145:
==Further reading==
* Berryman, Alan (2002) ''Population Cycles.'' Oxford University Press US. {{ISBN|0-19-514098-2}}
* [[Gerda de Vries|de Vries, Gerda]]; Hillen, Thomas; Lewis, Mark; Schonfisch, Birgitt and Muller, Johannes (2006) [https://books.google.com/books?id=jJH17hiqHLUC
* Haddon, Malcolm (2001) [https://books.google.com/books?id=TP_6Z4ukIZQC
* Hilborn, Ray and Walters, Carl J (1992) [https://books.google.com/books?id=WJg0OVEQHcQC
* McCallum, Hamish (2000) [https://books.google.com/books?id=r9KnI2kkQ30C
* Prevost E and Chaput G (2001) [https://books.google.com/books?id=4wdFFEMFupcC
* Plagányi, Éva, Models for an ecosystem approach to fisheries. FAO Fisheries Technical Paper. No. 477. Rome, FAO. 2007. 108p [http://www.fao.org/3/a1149e/a1149e.pdf]
* Quinn, Terrance J. II and Richard B. Deriso (1999) Quantitative Fish Dynamics.Oxford University Press {{ISBN | 0-19-507631-1}}
* Sparre, Per and Hart, Paul J B (2002) Handbook of Fish Biology and Fisheries, Chapter13: ''Choosing the best model for fisheries assessment.'' Blackwell Publishing. {{ISBN|0-632-06482-X}}
* [[Peter Turchin|Turchin, P.]] 2003. Complex Population Dynamics: a Theoretical/Empirical Synthesis. Princeton, NJ: Princeton University Press.
Line 193 ⟶ 160:
[[Category:Fisheries science]]
[[Category:Population ecology]]
[[Category:Population dynamics]]
| |||