Presentation on theme: "Positive and negative interactions Predation Interspecific competition Herbivory is a form of parasitism Competition is an interaction between individuals."— Presentation transcript:
Positive and negative interactions Predation Interspecific competition Herbivory is a form of parasitism Competition is an interaction between individuals of the same or of different species membership, in which the fitness of one is lowered by the presence of the other.
Amensalism is a relationship between individuals where some individuals are inhibited and others are unaffected. Parasitism is any relationship between two individuals in which one member benefits while the other is harmed but not killed or not allowed to reproduce. Mutualism is any relationship between two individuals of different species where both individuals benefit. Commensalism is a relationship between two individuals where one benefits and the other is not significantly affected. Symbiosis is any type of relationship where two individuals live together Parasitoidism is a relationship between two individuals in which one member benefits while the other is not allowed to reproduce or to develop further
Mutualism is the way two organisms of different species exist in a relationship in which each individual benefits. Mutualism is the oposite to interspecific competition. Client– service relationships Pollination Mutualism is often linked to co- evolutionary processes Facilitation is a special form of commensalism and describes a temporal relationship between two or more species where one species benefits from the prior (and recent) presence of others. Facilitation generally increases diversity. In plant succession early arriving plants pave the way for later arrviing by modifying soil condition.
Intraspecific competition Scramble (exploitation, diffuse) is a type of competition in which limited resources within an habitat result in decreased survival rates for all competitors. Mytilus edulis Contest (interference) competition is a form of competition where there is a winner and a loser Canis lupus Mate competition
Territoriality Territories imply a more or less even distribution of individuals in space Territoriality is a form of avoidance of intraspecific competition Territory Home range Overlap Home ranges might overlap The variance in distance is much less than the mean distance
The stem self thinning rule Trees is a forst have certain distances to each others Leaf area L increases with plant density N L= N where L is the average leaf area per plant. This area and mean plant weight w increase with stem diameter by =aD 2 and w=bD 2 Therefore Modified from Osawa and Allen (1993) Density dependent regulation and diffuse competition The -3/2 self thinning rule
Density independence Density dependence Density dependent regulation of population size results from intraspecific competition Vulpia fasciculata Density independence Density dependence Tribolium confusum Data from Ebert et al. 2000. Oecologia 122 Data from Bellows 1981. J. Anim. Ecol. 50
Density independence Density dependence K 1/rN t /N t+1 NtNt 1 First order order recursive function of density dependent population growth Nicholson and Baily model Salmo trutta Peak reproduction at intermediate densityy Data from Allen 1972, R. Int. Whaling Comm. 22.
Competitive exclusion principle Georgii Frantsevich Gause (1910-1986) In homogeneous stable environments competitive dominant species attain monodominancy. Paramecium aurelia Paramecium caudatum Joint occurrence Applying this principle to bacterial growth Gause found a number of antibiotics Data from Gause 1943, The Struggle for Existence
Interspecific competition Tribolium confusum Tribolium castaneum TemperatureHumidityPercentage wins Tribolium confusum Tribolium castaneum HotMoist0100 TemperateMoist1486 ColdMoist7129 HotDry9010 TemperateDry8713 ColdDry1000 Data from Park 1954. Phys. Zool. 27. Two species of the rice beetle Tribolium grown together compete differently in dependence on microclimatic conditions.
Alfred James Lotka (1880- 1949) Vito Volterra (1860-1940) The Lotka – Volterra model of interspecific competition At equilibrium: dN/dt = 0 If competitive strength differs one species vanishes If carrying capacity differs one species vanishes Certain conditions allow for coestistence The Lotka Volterra model predicts competitive exclusion
But the oberserved species richness is much higher than predicted by the model. The model needs stable reproductive rates stable carrying capacities stable competition coefficients It needs also homogeneous environments > K1 > K2 Randomy fluctuating values of r, K, , and . Unpredictability and changing environmental conditions as well as habitat heterogeneity and aggregation of individuals promote coexistence of many species. Grassland are highly diverse of potentially competing plants
Competition for enemy free space (apparent competition) Data from Bonsall and Hassell 1997, Nature 388 Plodia interpunctellaVenturia canescens Ephestia kuehniella Predator mediated competition might cause extinction of the weaker prey Extinction
Character displacement and competitive release Rhinoceros beetles Chalcosoma caucasus Chalcosoma atlas Interspecific competition might cause species to differ more in phenotype at where where they co-occur than at sites where they do not co-occur (character displacement) Interspecific competition might cause a lower phenotypic or ecological variability of two species at sites where both species compete. Competitive release is the expansion of species niches in the absence of interspecific competitors. Raven Raven + Crows Dietary width Bodey et al. 2009. Biol.Lett 5: 617 Raven
Predation Erigone atra Generalist predator Polyphages Specialist predator Monophages Canada lynx and snowshoe hare Oligophages
Trade-offs in foraging Searching time Prey quality Starvation Maximum yield Stopping point Animals should adopt a strategy to maximuze yield Optimal foraging theory 10 15 9 3 178 4 20 18 11 Parus major Great tits forage at site of different quality How long should a bird visit each site to have optimal yield? Predicted energy intake from travel time Predicted energy intake from travel and handling time Holling’s optimal foraging theory Cowie 1977
Hudson’s Bay Company Data from MacLulick 1937, Univ. Toronto Studies, Biol. Series 43 Data from Yoshida et al. 2003, Nature 424 Specialist predators and the respective prey often show cyclic population variability 12 year cycle Canada lynx and snowshoe hare Cycles of the predator follow that of the prey Cycles might be triggered by the internal dynamics of the predator – prey interactions or by external clocks that is environmental factors of regular appeareance Most important are regular climatic variations like El Nino, La Nina, NAO. Bracyonus calyciflorus Chlorella vulgaris
The Lotka Volterra approach to specialist predators The Lotka Volterra models predicts unstable delayed density dependent cycling of populations The equilibrium abundances of prey and predator e: mortality rate of the predator r: reproductive rate of the prey faN: reproductive rate of the predator f: predator efficieny aP: mortality rate of the prey a: attack rate In nature most predator prey relationships are more or less stable. Any deviation from the assumption of the Lotka Volterra model tends to stabilize population: Prey aggregration Density dependent consumption Functional responses
Environmental heterogeneity and predator prey cycles Eotetranychus sexmaculatus Typhlodromus occidentalis Simple unstructured environment Heterogeneous environment Habitat heterogeneity provides prey refuges and stabilizes predator and prey populations
Functional response Type II Holling responseType III Holling response Predator attak rates are not constant as in the Lotka Volterra model Calliphora vomitoriaMicroplitis croceipes Type I response Microplitis croceipes Calliphora vomitoria
Variability, chaos and predator prey fluctuations Lotka Volterra cycles with fixed parameters a, e, f, r. Lotka Volterra cycles with randomly fluctuating parameters a, e, f, r. Any factor that provides not too extreme variability into parameters of the predator prey interaction tends to stabilize populations. Fixed parameter values cause fast extinction. Stochasticity tends to stabilize populations Dynamic equilibrium
Herbivory Plant defenses against herbivors Alcaloide (amino acid derivatives): nicotine, caffeine, morphine, colchicine, ergolines, strychnine, and quinine Terpenoide, Flavonoids, Tannins Mechanical defenses: thorns, trichomes… Mimicry Mutualism: Ant attendance, spider attendance Digitalis Many plants produce secondary metabolites, known as allelochemicals, that influence the behavior, growth, or survival of herbivores. These chemical defenses can act as repellents or toxins to herbivores, or reduce plant digestibility.
Functions of herbivores in coral reefs Negative feedback loops occur when grazing is too low Increasing algal cover Decreasing coral recruitment Low coral cover Low grazing intensity Decreasing fish recruitment Reduced structural complexity Positive feedback loops occur when grazing is high Decreasing algal cover Increasing coral recruitment High coral cover High grazing intensity Increasing fish recruitment Increased structural complexity Herbivorous fish (Diadema) Overfishing of herbivorous fish might cause a shift to algal dominated low divesity communities Hay and Rasher (2010)