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upheld as long as these differences are accounted for. In accounting for this variety of competitive weights, animals distribute such that their competitive weights in each habitat match the proportion of resources present there. For example, in one experiment goldfish differing in competitive ability behaved in a way that maximized their intake rate relative to their competitive weight. Since the mean rank of fish in a site varied inversely with the total number of fish in both the high resource density site and the low resource density site, there was no correlation between competitive ability and time spent at the higher resource density site. As expected in an ideally distributed population of goldfish of different competitive abilities, the intake rate of each competitive weight did not differ between the sites.
255:
involved groups of participants choosing between blue and red cards in order to earn points towards prizes. When the groups’ choice of cards was graphed in relation to the ratios between the points, the slopes demonstrated some undermatching, which is a deviation from the
Matching Law. Undermatching is the situation when the ratio of foragers between two patches (in this case, how many people picked each card) is less than the ratio of resources between the two patches (the points each card is worth). The results show that the IFD could not predict the outcome. However, they also show that it is possible to apply the Ideal Free Distribution to group choice, if that group choice is motivated by the individuals’ tendencies to maximize
66:" implies that animals are aware of each patch's quality, and they choose to forage in the patch with the highest quality. The term "free" implies that animals are capable of moving unhindered from one patch to another. Although these assumptions are not always upheld in nature, there are still many experiments that have been performed in support of IFD, even if populations naturally deviate between patches before reaching IFD. IFD theory can still be used to analyze foraging behaviors of animals, whether those behaviors support IFD, or violate it.
189:, a species of social spiders, live together cooperatively and build large web communities. Number of insects caught decreases with increasing population due to surface area scaling, but prey mass increased due to larger webs. At intermediate population size of 1000, prey biomass per capita was maximized. The results correspond to observed results of population size and ecological conditions- areas that lack larger insects have smaller spider communities.
156:
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account for under-matching when the distribution is less extreme than the resource rate. When one patch is seen to have more preference over another, bias in the resource ratio is taken into consideration. These two matching relationships are assessed by a regression of the log ratio of the numbers at each site against the log ratio of resources at the site.
206:
from the distribution of the competitive weights. When exposed to a poor patch and a good patch, the fish distributed such that the payoffs per unit of competitive weight were the same at both patches. This experiment demonstrates that the incorporation of competitive weights into habitat selection can improve predictions of animal distributions.
146:. Various deviations may occur initially, but eventually the patches will accommodate the number of individuals that is proportional to the amount of resources they each contain. In this case, patches of equal intrinsic value allow for the same number of individuals in each patch. At this point, the state of the individuals is referred to as
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reproductive success, but the aphids settle in such a way that the average reproductive success for individuals on leaves with one, two, or three galls is the same. However, reproductive success is unequal within the same leaf, and stem mothers that settle closer to the base of the leaf have higher fitness than those that settle distally.
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less on the more resource abundant site. Knowledge of the competitive interactions, effects of travel between sites, number of animals in population, perceptual abilities of these animals, and the relative and absolute resource availability on each patch is required to accurately predict the distribution of a foraging population.
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The results they found do not support IFD predictions and some take this outcome to mean that the current model is too simple. Animal behaviorists have proposed a modification to the model that denotes an ultimate outcome of a population always having more individuals on the least profitable site and
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In experiments that test the predictions of IFD, most often there tends to be more individuals in the least profitable patch and a shortage at the richest patch. This distribution is found across species of insects, fish and birds. However, modifications to the original assumptions have been made and
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distributions that each maintains ideal free distribution. For example, if good competitors forage twice as well as poor competitors, a possible scenario upholding IFD would be for four good competitors and eight poor competitors to forage at a given site, each gaining the same net payoff per unit of
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Bumblebees distribute themselves systematically so that there was an equalization of gain per flower (the currency) in flowers of different nectar production. Bees were also distributed proportionally based on plant density and differential nectar distribution. In Selous wild dogs, observed pack size
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Additionally, foraging behavior in coho salmon does not uphold ideal free distribution predicted by the equal competitors model, but does uphold ideal free distribution with the inclusion of competitive inequalities. In other words, the distribution of the number of fish was significantly different
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It is important to keep in mind that IFD does rely on the assumptions previously stated and that all of these qualities are probably not met in the wild. Some believe that tests of IFD are not executed properly and therefore yield results that appear to follow the prediction but in reality do not.
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The ideal free distribution hypothesis assumes that all individuals are equal in competitive abilities. However, there is experimental evidence that demonstrates that even when the competitive abilities, or weights, of individuals in a population differ, the ideal free distribution is still mostly
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despite the fact that there is an unequal number of competitors in each patch. This equilibrium is demonstrated as the red line in Figure 1, where the feeding rate is the same for all individuals even though there are 5 individuals in Patch A and 8 individuals in Patch B. From the figure, we can
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However, this prediction assumes that each individual will act on its own. It does not hold for situations involving group choice, which is an example of social behavior. In 2001, Kraft et al. performed an experiment that tested the IFD's predictions of group choice using humans. This experiment
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in order to reanalyze IFD experiments. When psychologists perform tests of this law, they use more sensitive measures to account for deviation from strict matching relationships. Kennedy and Gray utilize this method to test the validity of previous IFD experiments. Using this analysis, they can
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has also been shown to generally follow the Ideal Free
Distribution. After hatching in the spring, female aphids compete with each other for galling sites closest to the stems of the largest leaves. Both settling on a smaller leaf and sharing a leaf with another aphid reduce a stem mother's
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For patches with unequal innate values, or intrinsic values, we can still apply the same distribution principle. However, it is predicted that the number of individuals in each patch will differ, as the amount of resources in each patch will be unequal. They will still reach
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of individual choice, which states that an individual's rate of response will be proportional to the positive reinforcement that individual receives for that response. So an animal will go to the patch that provides the most benefits to them.
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infer that the first 6 foragers settle in Patch B due to its greater intrinsic quality, but the increased competition causes the lesser quality Patch A to be more beneficial for the seventh individual. This figure is depicting the
89:
that is determined by the amount of resources available in each patch. Given that there is not yet any competition in each patch, individuals can assess the quality of each patch based merely on the resources available.
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Though the Ideal Free
Distribution can be used to explain the behaviors of several species, it is not a perfect model. There remain many situations in which the IFD does not accurately predict the behavioral outcome.
527:
Kennedy, M., & Gray, R. D. (1993). Can ecological theory predict the distribution of foraging animals? a critical analysis of experiments on the ideal free distribution. Oikos, 68(1), 158-166. Retrieved from
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As an optimal foraging model, the Ideal Free
Distribution predicts that the ratio of individuals between two foraging sites will match the ratio of resources in those two sites. This prediction is similar to the
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One experiment displayed this violation of IFD in stickleback fish. He saw that the actual observations and the ones stated by IFD were not congruent. More fish tended to disperse in the patch with less
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competitive weight. Additional combinations upholding IFD could exist as well. Even when individuals move between patches in a suboptimal fashion, this distribution of possible equilibria is unaffected.
549:
Godin, J.-G. & Keenleyside, M.H.A. 1984. Foraging on patchily distributed prey by a chichlid fish (Teleostei
Cichlidae): a test of the ideal free distribution theory. Animal Behaviour 32: 120-131.
508:
Kraft, J. R., Baum, W. M., & Burge, M. J. (2002). Group choice and individual choices: modeling human social behavior with the ideal free distribution. Behavioural
Processes, 57(2-3), 227-240.
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to move to the highest quality patch. However, this can be violated by dominant individuals within a species who may keep a weaker individual from reaching the ideal patch.
438:
Sutherland, W.J., C.R. Townsend, and J.M. Patmore. "A test of the ideal free distribution with unequal competitors." Behavioral
Ecology and Sociobiology. 23.1 (1988): 51-53.
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did not agree with results of daily per capita food intake. However, when factoring in distance traveled to hunt into the currency, observed pack size was close to optimal.
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Yip, E., Powers, K., & Aviles, L. (2008). Cooperative capture of large prey solves scaling challenge faced by spider societies. PNAS, 105(33), 11818-11822.
354:
Fretwell, S. D. & Lucas, H. L., Jr. 1969. On territorial behavior and other factors influencing habitat distribution in birds. I. Theoretical
Development.
152:. Once the individuals are in Nash equilibrium, any migration to a different patch will be disadvantageous since all individuals obtain the same benefits.
55:
to the amount of resources available in each. For example, if patch A contains twice as many resources as patch B, there will be twice as many individuals
447:
Grand, Tamara. "Foraging site selection by juvenile coho salmon: ideal free distributions of unequal competitors." Animal
Behavior. 53.1 (1997): 185-196.
499:
Ruxton, Graeme, and Stuart
Humphries. "Multiple ideal free distributions of unequal competitors." Evolutionary Ecology Research. 1.5 (1999): 635-640.
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Abraham, J.N. (2005). Insect choice and floral size dimorphism: Sexual selection or natural selection? Journal of Insect Behavior, 18(6), 743–756.
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Once the assumptions are met, IFD theory predicts that a population of individuals will distribute themselves equally among patches with the
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Creel & Creel. (1995). Communal hunting and pack size in African wild dogs, Lycaon pictus. Animal Behaviour, 50(5), 1325-1339.
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Variations in competitive abilities of individuals in a given population also tend to result in several different possible
173:, through which the ratio of individuals at the patches corresponds to the ratio of resources available in those patches.
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Milinski, M. 1979. An evolutionarily stable feeding strategy in sticklebacks. Zietschrit fur Tierpsychologie 51: 36-40.
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Population Ecology of Individuals chapter on Whitham's 1980 study regarding aphids and the ideal free distribution.
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Whitham, Thomas G. (April 1980). "The Theory of Habitat Selection: Examined and Extended Using Pemphigus Aphids".
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Increasing the number of individuals in a given patch reduces the quality of that patch, through either increased
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Danchin, E., Giraldeau, L.-A., & CĂ©zilly, F. (2008). Behavioural ecology. Oxford: Oxford University Press.
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also displayed the same subtle difference in predicted vs. actual dispersal numbers in relation to resources.
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The ideal free distribution theory is based on several assumptions and predictions as indicated below;
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This causes animal behaviorists to be split in opinions of whether IFD is a true phenomenon or not.
51:. The theory states that the number of individual animals that will aggregate in various patches is
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280:(the sought after food source) and the more abundant patch had a shortage of visitors.
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The ideal free distribution when the resource is variable – Introduction
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Individuals are aware of the value of each patch so that they can choose the
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Dreisig, H. (1995). Ideal free distributions of nectar foraging bumblebees.
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134:, so they are all equally able to forage and choose the ideal patch.
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s individuals distribute themselves among several patches of
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325:(organism, bee, that exhibits Ideal Free Distribution)
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213:stem mothers for galling sites on the leaves of
272:are implemented in experiments involving IFD.
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345:. Princeton, NJ: Princeton University Press.
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1555:Latitudinal gradients in species diversity
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411:https://doi.org/10.1007/s10905-005-8737-1
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1453:Predator–prey (Lotka–Volterra) equations
1092:Tritrophic interactions in plant defense
209:In another example, competition between
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1485:Random generalized Lotka–Volterra model
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521:
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263:Experimental data not in support of IFD
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1293:Herbivore adaptations to plant defense
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343:Populations in a Seasonal Environment
1308:Predator avoidance in schooling fish
530:https://www.jstor.org/stable/3545322
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399:https://www.jstor.org/stable/3546218
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1758:Intermediate disturbance hypothesis
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1511:Ecological effects of biodiversity
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28:) is a theoretical way in which a
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2157:
847:Generalist and specialist species
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1570:Occupancy–abundance relationship
1590:Relative abundance distribution
1303:Plant defense against herbivory
1170:Competitive exclusion principle
882:Mesopredator release hypothesis
231:
1175:Consumer–resource interactions
287:Kennedy and Gray utilized the
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1:
2021:Biological data visualization
1848:Environmental niche modelling
1575:Population viability analysis
514:10.1016/S0376-6357(02)00016-5
329:
1506:Density-dependent inhibition
427:10.1016/0003-3472(95)80048-4
85:Each available patch has an
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1975:Liebig's law of the minimum
1810:Resource selection function
701:Metabolic theory of ecology
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70:Assumptions and predictions
10:
2162:
1875:Niche apportionment models
1595:Relative species abundance
799:Primary nutritional groups
696:List of feeding behaviours
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59:in patch A as in patch B.
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2056:Ecosystem based fisheries
1998:
1898:
1823:
1696:
1668:Interspecific competition
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1560:Minimum viable population
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1418:Maximum sustainable yield
1403:Intraspecific competition
1398:Effective population size
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1278:Anti-predator adaptations
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789:Photosynthetic efficiency
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2046:Ecological stoichiometry
2011:Alternative stable state
122:interference competition
1890:Ontogenetic niche shift
1753:Ideal free distribution
1663:Ecological facilitation
1413:Malthusian growth model
1383:Consumer-resource model
1240:Paradox of the plankton
1205:Energy systems language
925:Chemoorganoheterotrophy
892:Optimal foraging theory
867:Heterotrophic nutrition
459:The American Naturalist
382:10.1073/pnas.0710603105
316:Optimal foraging theory
171:habitat matching effect
43:, in order to minimize
22:ideal free distribution
2036:Ecological forecasting
1980:Marginal value theorem
1778:Landscape epidemiology
1713:Cross-boundary subsidy
1648:Biological interaction
998:Microbial intelligence
686:Green world hypothesis
341:Fretwell, S. D. 1972.
311:Marginal value theorem
257:positive reinforcement
241:Deviation from the IFD
160:
2041:Ecological humanities
1940:Ecological energetics
1885:Niche differentiation
1748:Habitat fragmentation
1516:Ecological extinction
1463:Small population size
1215:Feed conversion ratio
1195:Ecological succession
1127:San Francisco Estuary
1041:Ecological efficiency
983:Microbial cooperation
158:
2066:Evolutionary ecology
2031:Ecological footprint
2026:Ecological economics
1950:Ecological threshold
1945:Ecological indicator
1815:Source–sink dynamics
1768:Land change modeling
1763:Insular biogeography
1615:Species distribution
1354:Modelling ecosystems
1013:Microbial metabolism
852:Intraguild predation
641:Biogeochemical cycle
607:Modelling ecosystems
216:Populus angustifolia
211:sugarbeet root aphid
144:same intrinsic value
130:All individuals are
118:scramble competition
45:resource competition
2116:Theoretical ecology
2091:Natural environment
1955:Ecosystem diversity
1925:Ecological collapse
1915:Bateman's principle
1870:Limiting similarity
1783:Landscape limnology
1605:Species homogeneity
1443:Population modeling
1438:Population dynamics
1255:Trophic state index
306:Behavioural ecology
197:Unequal competitors
132:competitively equal
2146:Population ecology
2127:Outline of ecology
2076:Industrial ecology
2071:Functional ecology
1935:Ecological deficit
1880:Niche construction
1843:Ecosystem engineer
1620:Species–area curve
1541:Introduced species
1356:: Other components
1288:Deimatic behaviour
1190:Ecological network
1122:North Pacific Gyre
1107:hydrothermal vents
1046:Ecological pyramid
993:Microbial food web
804:Primary production
749:Foundation species
397:, 72(2), 161-172.
356:Acta Biotheoretica
187:Anelosimus eximius
161:
87:individual quality
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2016:Balance of nature
1773:Landscape ecology
1658:Community ecology
1600:Species diversity
1536:Indicator species
1531:Gradient analysis
1408:Logistic function
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1273:Animal coloration
1250:Trophic mutualism
988:Microbial ecology
779:Photoheterotrophs
764:Myco-heterotrophy
676:Ecosystem ecology
661:Carrying capacity
626:Abiotic component
322:Xylocopa sonorina
182:Experimental data
2153:
1833:Ecological niche
1805:selection theory
1625:Umbrella species
1610:Species richness
1546:Invasive species
1526:Flagship species
1433:Population cycle
1428:Overexploitation
1393:Ecological yield
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1225:Mesotrophic soil
1165:Climax community
1097:Marine food webs
1036:Biomagnification
837:Chemoorganotroph
691:Keystone species
651:Biotic component
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225:Nash equilibrium
166:Nash equilibrium
149:Nash equilibrium
96:Individuals are
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1965:Extinction debt
1930:Ecological debt
1920:Bioluminescence
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1863:marine habitats
1838:Ecological trap
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556:External links
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822:Apex predator
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47:and maximize
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39:within their
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27:
23:
19:
2096:Regime shift
2081:Macroecology
1802:
1798:
1752:
1738:Edge effects
1708:Biogeography
1653:Commensalism
1501:Biodiversity
1378:Allee effect
1117:kelp forests
1070:Example webs
935:Detritivores
774:Organotrophs
754:Kinetotrophs
706:Productivity
545:
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342:
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294:
289:matching law
286:
282:Cichlid fish
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248:Matching Law
244:
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232:Shortcomings
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53:proportional
25:
21:
15:
1733:Disturbance
1636:interaction
1458:Recruitment
1388:Depensation
1180:Copiotrophs
1051:Energy flow
973:Lithotrophy
917:Decomposers
897:Planktivore
872:Insectivore
862:Heterotroph
827:Bacterivore
794:Phototrophs
744:Chemotrophs
716:Restoration
666:Competition
138:Predictions
78:Assumptions
41:environment
2101:Sexecology
1678:Parasitism
1643:Antibiosis
1478:Resistance
1473:Resilience
1363:Population
1283:Camouflage
1235:Oligotroph
1150:Ascendency
1112:intertidal
1102:cold seeps
1056:Food chain
857:Herbivores
832:Carnivores
759:Mixotrophs
734:Autotrophs
613:components
330:References
62:The term "
30:population
2006:Allometry
1960:Emergence
1688:Symbiosis
1673:Mutualism
1468:Stability
1373:Abundance
1185:Dominance
1143:Processes
1132:tide pool
1028:Food webs
902:Predation
887:Omnivores
814:Consumers
769:Mycotroph
726:Producers
671:Ecosystem
636:Behaviour
37:resources
2140:Category
2061:Endolith
1990:Xerosere
1902:networks
1718:Ecocline
1264:Defense,
940:Detritus
842:Foraging
711:Resource
487:83753051
300:See also
159:Figure 1
57:foraging
2051:Ecopath
1858:Habitat
1728:Ecotype
1723:Ecotone
1700:ecology
1698:Spatial
1634:Species
1494:Species
1365:ecology
1350:Ecology
1298:Mimicry
1266:counter
1210:f-ratio
958:Archaea
646:Biomass
619:General
611:Trophic
603:Ecology
479:2460478
278:daphnia
177:Support
110:patch.
49:fitness
18:ecology
1082:Rivers
978:Marine
485:
477:
1999:Other
1900:Other
1853:Guild
1825:Niche
1077:Lakes
483:S2CID
475:JSTOR
395:Oikos
108:ideal
64:ideal
33:'
20:, an
1087:Soil
98:free
510:doi
467:doi
463:115
423:doi
378:doi
26:IFD
16:In
2142::
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1352::
609::
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520:^
481:.
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461:.
259:.
128:5)
124:.
114:4)
104:3)
94:2)
83:1)
1803:K
1801:/
1799:r
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1335:t
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595:e
588:t
581:v
512::
489:.
469::
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425::
384:.
380::
24:(
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