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244 Cards in this Set
- Front
- Back
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Population ecology
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Cause and effect of the abundance of a population
Growth, persistence, human effects, extinction |
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Demographic processes
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Birth, death, immigration, emigration
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Fecundity
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b, average number of offspring per individual per year
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Per capita death rate
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d, proportion of individuals which die each year
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Survival rate
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s = 1 - d
Proportion that survive per year |
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Net reproduction rate
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R = births (b) + survival (s)
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Environmental stochasticity
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Unpredictable environment changes
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Demographic stochasticity
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Random differences among individuals in survival and reproduction
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Rate of change of abundance
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Birth rate - death rate
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Causes of density dependent birth and death rate
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Food supply, territories, space, cannibalism, stress, predators, parasites
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Intraspecific competition
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Similar requirements for survival/growth/reproduction
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Scramble/exploitation competition
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Limited resource shared equally
E.g. less grazing Intensity incr gradually: affects growth/development then survival/reproduction |
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Contest/interference competition
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Limited resource shared unequally
E.g. territory Direct inhibition of growth/reproduction/transmission E.g. bacteria toxins killing other strains |
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Law of constant final yield
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Total biomass of plants regulated not the number of individuals
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Example of density reducing reproduction
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Harp seals become reproductive at 87% mature body weight
Density reduces growth rate and increases age of sexual maturity |
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Self-thinning
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Density of plants decline and individuals weight increases in unison
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Recruitment
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Individuals survive and are added to the population
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Overlapping generation logistic equations
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dN/dt = rN(1- n/k)
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Discrete generation logistic equation
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Nt+1 = Nt + rNt (1- Nt/K)
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Growth time lags
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Conditions L generations ago affect now
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Allee effect
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Inverse density dependence
Growth of a small population declines as it gets smaller, will go extinct below threshold Difficult to find mates, disease due to inbreeding, lack of social defence |
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Stage structured model
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Remain in one stage until they acquire characters of the next
E.g. size, developmental stage |
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Age structured model
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Age correlates with life history
Equal time intervals |
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Life tables
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Follows a cohort
Record number surviving each year Age specific mortality and survival schedules |
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lx
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Proportion of original population surviving to age x
Survivorship |
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dx
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Number that died between ages x and x+1
age specific mortality |
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qx
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Age specific mortality rate
dx/nx |
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Type 1 survivorship curve
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Individuals live out physiological life span
High initial survival then heavy mortality Humans |
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Type 2 survivorship curve
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Survival rates don't vary with age
Birds |
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Type 3 survivorship curve
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High initial mortality
Fish |
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Time-specific / static life table
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Sample a distribution of age classes at a single time
Easier to construct Assumes each age class sampled in proportion to it's abundance |
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bx
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Average number of female offspring born to a female of age x
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Gross reproductive rate
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Total bx
Average number of female offspring born to a female if she lived to that age |
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Net reproductive rate
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R, Average number of female offspring born to a female over her lifetime
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Spatial variation in environmental factors
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Soil condition, elevation, vegetation, water depth
Fire, drought, flood, epidemic |
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Reasons for dispersal
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Intense competition, direct interference, avoiding kin competition, avoid inbreeding, big groups attract predators
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Metapopulation
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Middle of the scale between no dispersal and free and frequent dispersal
Discrete patches of suitable habitat Large populations can still go extinct Local populations not synchronised |
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m
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Probability of a successful recolonisation of an empty patch
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μ
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Probability that a single patch goes extinct per unit time
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μp
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Rate that occupied patches go extinct
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mp(1-p)
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Recolonisation rate of empty patches
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Habitat heterogeneity
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Larger patches can have a larger habitat diversity
Increasing area reduces temporal variability |
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The rescue effect
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Risk of extinction declines with abundance
Higher immigration to patches Greater proportion of occupied patches Larger subpopulations Positive feedback |
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Source population
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Favourable: births > deaths
Emigration to sink |
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Sink population
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Unfavourable: deaths > births
Immigration from source |
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Demography
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Study of size, structure, distribution of human populations.
Spatial/temporal changes in response to birth/death/migration |
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Recognising individuals
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Photo databases, colouration and pattern, mark artificially with tag/collar/ring
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Age structure
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Survival/reproduction/density/stochastic effects differ in age classes. Variation of survival/reproduction/migration with age/sex.
Lambs/yearlings/2-6yr/>6yr. Relationship between survival and density/weather for each class |
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Life tables
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Summarise age-specific variation, survival and fecundity, estimate population parameters (Ro, T, intrinsic rate of increase)
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Cohort-based
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Follow a group, difficult, births differ in life table properties
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Cross-sectional
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Sample population and estimate ages
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Ix
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Proportion of original cohort surviving
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mx
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Average number of recruits per age group in life table
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Generation length (T) =
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age x (Ix) x (mx) / Ro
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Rate of population increase (r) =
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ln(Ro) / T
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λ
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Change in population size between 2 time steps
<1 = decrease, >1 = increase |
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Matrix models
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Combines age/stage vital rates
Calculates what is expected the next year from each age class - transition matrix |
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Soay sheep life history
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Born April, gain condition in summer and spring, females recover from birth in late summer, males rut in November, lose condition in autumn and winter, mortality towards end of winter
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St Kilda
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Humans evacuated 1930, primitive sheep breed, 100 to Hirta in 1930 and all blackface sheep removed, whole island counts since 1955, no predators or management
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Soay sheep
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Sexually dimorphic (M 45kg, F up to 30)
Life-span: F 16y, M 11y Highly polygynous |
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Soay data collection
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Regular census, lambs caught/weighed/marked, August catch-up (bay sheep caught and whole island counted), fights/matings in rut, fecundity/dispersal/survival/population size, exact birth and death dates, all breeding attempts
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Soay intrinsic factors: Overcompensatory density dependence
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Intense, initial density increase exceeds carrying capacity and pushes down final density, survival is depressed at high density, structured model creates a cycle unlike reality but adding a constant survival rate above a threshold makes it more accurate
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Soay extrinsic factors
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Strong density correlation with breed on different island, environment effects, density doesn't explain above a threshold, March gales and wet/windy winters, interaction between intrinsic and extrinsic factors, explains 21% variation in pop. growth
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Lambs
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Invest more reserves in growth, larger surface area to volume ratio, lose out in intra-specific competition to older, mortality due to density and winter weather
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Adult male sheep
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Large energy expended during rut, lose condition, mortality in winter weather
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Adult female sheep
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Large energy expended during late winter/early spring during late gestation and lactation, enter winter in good condition, mortality with end of winter weather
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Weather and sheep mortality
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Large-scale climate (NAO) predicts mortality better than local weather, captures combined effects of wind/rain/temp better than a single measure, winter weather interacts with density, pattern of mortality varies across years, early death pulse associated with lower overall mortality
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Predation
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One species benefits, other negative
Functional: True, grazing, parasites, parasitoids Taxonomic: carnivores, herbivores, omnivored Whole/partial consumption where prey is initially alive Interspecific, reduces density, disrupts competitive exclusion, pervasive effects |
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Ammensalism
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One species unaffected, other negative
E.g. elephant trampling plants |
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Competition
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Both species negative, both get less resources than if they were alone
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Neutralism
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Both no effect
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Mutualism
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Both species benefit, usually direct exchange, food/defence/transport, novel capabilities by at least 1 partner, don't need to be close, not selfless or without cost - net effect is positive, most of worlds biomass
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Commensalism
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One species benefits, the other unaffected
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Facultative mutualism
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Not species specific, both can survive without
Bumblebee and goldenrod plant, many other pollinators |
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Obligate mutualism
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Species-specific, can't survive without the other
Leaf-cutter ants and fungus: ants provide leaves/remove bacteria/invaders/chew wax off leaves/provide stable environment, fungus provides food for ants and digests plant chemicals to make them harmless |
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Symbiosis
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2 species living together, close physical associations, one benefits and other +/-/0, one host and one symbiont
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Behavioural mutualists
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No intimate symbiosis, each behaves in a way to benefit the other, protectors, dispersal of seeds/pollen, farming
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Mutualistic protectors
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Cleaner and client fish, feed on ectoparasites/bacteria/necrotic tissue from the body/surface of the client, client gains protection from infection and cleaner gains food
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Ant-plant mutualisms
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Ants provide protection by snipping off nearby shoots and protection from herbivores, plant provides food (extrafloral nectaries) and nesting sites, evolved many times in same plant family.
Amazonian canopy tree and stinging ant |
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Mutualistic seed dispersal
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Birds and animals disperse seeds of higher plants, animals digest fruit fast and seed moved to new site, plant needs to make thick coat to protect seed, rarely specific to animal/bird as plants rarely flower all year to provide a reliable food source
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Mutualistic pollen dispersal
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Hummingbirds/bats/small rodents/marsupials/insect benefit from nectar/pollen, plant gets efficient transfer to plants of same species, can transmit sexual diseases
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Mutualistic farming by humans
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Reliable food source, species cultivated and protected at expense of wild species
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Mutualistic farming by ants
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Termite/beetle/ant, milk lycaenid caterpillars for sugary excretion, caterpillar protected from predation/parasitoids, ants farm aphids for honeydew, aphids protected but larger when no ants and no predators
Proved by lower aphid survival when no ants on tree |
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Insect-mycetocyte symbiosis
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10% insects have intracellular maternally inherited microbes restricted to cytoplasm of mycetocyte cells of bacteriocyte in haemocoel, obligate association
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Insects nutritionally unbalanced diet
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Plant sap (phloem, xylem)
Vertebrate blood (tsetse flies) Timber (beetles) |
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Insect-microbe symbiosis
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Aphids and buchnera
Mycetocytes in aphid body cavity provide amino acids, grow slowly with no offspring without bacteria, bacteria never found alone |
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Mycorrhiza fungus
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Higher plants/ferns/mosses, captures nutrients from soil and transports to plants via roots, fungi gain carbon, ecologically obligate (can survive if unlimited nutrients and water), trophic benefit
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Arbuscular mycorrhiza
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2/3 plant species, mostly non-woody and tropical trees, hyphae grow between root cells and enter forming a branches arbuscule, extract N and P from soil, protects against pathogens and herbivory, confers resistance to toxic metals
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Ecto-mycorrhiza
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Boreal/temperate forest trees and shrubs, sheath around root that stunts growth, mycelium penetrates root and forms hartig net, large surface area for water/nutrient exhange, hyphae radiate onto litter layer
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Ericoid mycorrhiza
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Dominant heathland species, form dense coils on outside of root, hair-roots at soil surface, extract P/nitrate/ammonium/phosphate ions from detritus
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Lichens
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Fungus (mycobiont) and green algae/cyanobacterium (photobiont), mutualistic, onhospitable environments, phobiont photosynthesises C and cyanobacteria produces ammonium from N2 by N-fixing, mycobiont protects from sun exposure or absorbs minerals
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Nitrogen-fixing
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Rhizobia and leguminous plants, roots stimulate growth and form nodules to fix N2 from atmosphere which is used to synthesise amino acids and nucleotides, plant supplies sugars to breakdown N2, malate (breakdown product) provides C for rhizobia
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Vertebrate gut
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Gastrointestinal tracts of vertebrates populated by mutualistic microbiota, microbes gain substrates for growth, hosts gain short-chain fatty acids from food they couldn't digest, bacteria ferment cellulose/carbs/starch within mucus, convert N-compounds
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Ruminant gut
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3 part forestomach, bacteria and protozoa, oblogate anaerobic bacteria ferment cellulose, protozoa digest cellulose/interact with bacteria/consume bacteria/predate other protozoa
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Human microbiome
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Microbe community, genomes, environment interactions, project to understand link with health and disease, oral/skin/gut/vaginal/nasal/lung,
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True predators
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Kill prey immediately after attack, often consume whole, kill several or many different during lifetime
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Grazers
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Harmful but rarely lethal, remove part of prey, attack huge numbers during lifetime
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Parasites
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Consume part of prey (host), sometimes lethal, few individuals during lifetime, intimate relationship
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Parasitoids
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Insects (diptera, hymenoptera), free-living adults, lay eggs in/near other insects, larvae do little harm, usually kills as it emerges, intimate, not immediate death but do kill
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Prey protection
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Camouflage, crypsis, catalepsis, aggression, counter-attack, armour, bluffing, masting, vigilance
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Catalepsis
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Frozen posture with appendages retracted
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Sea lamprey and trout prey
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Trout population decreased dramatically when lamprey blocked from Great Lakes
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Cheetah and Thomson's gazelle
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Not always random sample, younger easier to catch with lower speed and stamina, fail to recognise predators
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Wolf/lynx and caribou
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Caribou density much higher and more stable where no predators on Slate Islands
Predators suppress prey |
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Wood mice/bank vole and tawny owl
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Populations continue to fluctuate even when tawny owl steadily increases
No effects |
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Snowshoe hare and lynx
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Oscillations in prey populations
Low food - hare more susceptible to predation Lynx appear to track hare cycles not generate |
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Lotka-Volterra Predator-Prey Model
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dn/dt = rN - aNP
dp/dt = faNP - qP r=reproduction rate, q= predator death rate f=predator assimilation, a=predator attack rate Can coexist when interspecific competition is lower than intraspecific |
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Lotka-Volterra assumptions
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Prey increases exponentially when no predators, predators only die due to natural causes, predation rate constant, predator reproduction rate depends on number of prey consumed
No time lags/migration/spatial structure/age structure/intraspecific comp |
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Lotka-volterra: r
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Prey growth rate
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Lotka-volterra: a
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Predator attack rate
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Lotka-volterra: f
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Predator conversion efficiency
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Lotka-volterra: q
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Predator death rate
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Prey or predator isocline
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Where prey or predator abundance doesn't change
dN/dt = 0 |
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Phase-plane analysis
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Predator along Y axis and prey along X, raw predator and prey isoclines, arrows indicate direction of change, typical trajectory
Creates cycles, predators lag behind prey Too simple, sensitive, extinctions, unstable, natural randomness |
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Intra-specific competition
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Populations move towards carrying capacity
dN/dt = rN (1- N/K) - aPN Weak comp creates decaying oscillations Strong comp creates no oscillations |
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Predator functional responses
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Relationship between per capita rate of consumption and prey abundance
Type 1 (linear), type 2 (plateau), type 3 (sigmoidal) |
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Type 1 predator functional response
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Linear
Attack rate increases with prey density Can eat unlimited, unrealistic Neutrally stable cycles, perpendicular isoclines |
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Type 2 predator functional response
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Predators take time to catch and devour - handling time, constant
Easier to find when more abundant, consumption plateaus, most common Divergent oscillations, destabilising Divides equations by 1=aThN |
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Type 3 predator functional response
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Sigmodial, predators can switch prey at low density and reduce handling at high density
More efficient at high density as learn search image of prey |
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Fragile communities sensitive to:
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Perturbations: species invasion/loss, climate change, pollution
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Trophic positions
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Basal, intermediate, top predators
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Source web
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Relations among species from 1 food source
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Sink web
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Relations among species with 1 top predator
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Connectance (C)
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How many of possible links are present
L/(S(S-1)/2) L=number undirected links S=number species |
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Linkage density (LD)
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Average number of links per species
L/S |
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Compartmentalisation
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Extent to which a food web contains relatively isolated subwebs
Stabilises communities More stable for given S/C/i values Likely in large communities which span habitats Difficult to detect when habitats aren't distinct or looking within a habitat |
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Trophic level
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Number of links +1 between basal species and one of interest
2-5 levels, average of 3 Energy flow, dynamic fragility, predator constraints |
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Omnivory
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Species feeds on prey from more than one trophic level
Same or different chain |
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Web patterns
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Constant predator/prey ratio (~4:3), 3 species loops uncommon, linkage density constant, proportion of links relatively constant, food chains short, omnivory infrequent, not strong compartments
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Mathematical definition of community stability
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Based on ability to defy change, resilience
Resistance: withstand perturbation Stability: response to perturbation Local and global stability |
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Empirical definition of community stability
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Observations
Demographic approach Degree of fluctuation over time Response after species loss/gain or abiotic changes |
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Elton and MacArthur: Stability increase as links increase
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More species, more interactions, more paths for energy transfer, loss only affects part of community (buffered)
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May, 1972
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Mathematical model of hypothetical communities
Relationship between species number, connectance, mean interaction strength Webs drawn at random stability measured Stable if i√SC<1 Random assemblages, predators without prey, difficult to compare to reality, differences measuring s/i |
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Briand 1983
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Meta-analysis of 40 webs
Connectance decreased with species number |
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Weak web links
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Promote species persistence and stability
Dampen oscillations of strong couples More stable if weak links dominate |
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Small world structure
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Mainly weak links
Connected to few others |
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Energy flow restricting number of trophic levels
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Small amount radiant energy fixed by photosynthesis
1-30% passed on at each level Extra level not viable Predicts high productivity allows more levels but this not seen |
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Dynamic fragility restricting number of trophic levels
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Long chains have major fluctuations
Return time faster with fewer levels Top predators go extinct in variable environments Less intra-specific competition when more levels, less stable communities |
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Predator constraints restricting number of trophic levels
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Larger/faster or smaller/stealthier than prey
Body size and home range increase with level Limit to size and speed Lower prey have higher nutritional value Top predators too rare to be viable |
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Indirect food web effects
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One species (donor) influencing another (receiver) via a third (transmitter)
Common in complex communities |
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Apparent competition
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Multiple non-competing prey species elevated the number of predators and increases the predation pressure
Via a common enemy: parasites on immune system effect other parasites |
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Trophic cascade
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Effects at one level influence abundance of species at other not directly connected levels
Top-down or bottom-up effects |
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Tri-tropic effects
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Effect top-down or bottom-up
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Keystone species
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Tightly connected, removal creates significant effect
Unexpected complex indirected effects - No cat causes mice and bird to go extinct |
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Disease
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Humans: semi-permanent, negative effect on well-being, discomfort, illness
Other organisms: semi-permanent, negative effect on survival, reproduction Pathology caused by infection |
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Macroparasites
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Worms, fleas
Adults don't replicate in host Count number - burden Determine severity and immunity level |
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Microparasites
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Viruses, bacteria
Replicate in host Count number of susceptible/infected/recovered |
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Types of parasite and pathogen
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Bacteria (staphylococcus aureus)
Viruses (HIV) Proteins (prions) Protozoa (plasmodium) Helminths (tapeworm) Fungi (ringworm) |
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Host-centric disease questions
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How is it transmitted? How many hosts get sick? Epidemics be prevented? Disease be eradicated? Predict immunisation success? Disease regulate host populations?
Tracks dynamics at host level |
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Parasite-centric disease questions
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Host/parasite densities change over infection? Parasite density limits? Immunity? Interaction causing symptoms? Drugs/vaccination?
Tracks at parasite and host cell level |
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SIR models
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S=susceptible
I=infected R=recovered Alpha=deaths due to disease Beta=transmission coefficient Gamma=recovery rate |
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SIR model assumptions
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Clear once recovered for life
Uninfected at birth Fecundity not affected |
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Equation for SIR model susceptible individuals
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ds/dt = b(S(t)+I(t)+R(t)) - dS(t) - betaS(t)I(t)
ds/dt= births - natural deaths - rate become infected |
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Equation for SIR model infected individuals
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dI/dt = betaS(t)I(t) - dI(t) - alphaI(t) - gammaI(t)
dI/dt = infection rate - infected natural deaths - infected disease deaths - recovered |
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Equation for SIR model recovered individuals
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dR/dt = gammaI(t) - dR(t)
dR/dt = recovery rate - natural deaths |
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Epidemic curve
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Disease spreads and more hosts become resistant
High resistance and low number susceptible - dies out Ebola virus Number infected hosts must increase for epidemic to spread |
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Threshold density
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Lowest population size in which an epidemic can still spread
Viruses in Serengeti lions coincided with susceptible numbers born |
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Basic reproductive number (Ro)
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>1: invasion <1: cannot invade
Ro = number new infections x infection duration betaS/d+alpha+gamma > 1 Equivalent to pathogen fitness/birth rate of new infections from 1 individual Number infected must increase to spread epidemic Increases with transmission rate/host density Recreases with virulence/host death/recovery |
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Herd immunity
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Vaccinating to protect population from epidemic
Decrease susceptible hosts below threshold for disease increase Ro < 1 |
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Ro in microparasites
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Average number new infections from a single host introduced into a population of uninfected
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Ro in macroparasites
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Average number of mature offspring produced by a mature parasite through life in a population of uninfected hosts
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Parasites as predators
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Resource availability controls dynamics
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Parasites as prey
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Immune response controls dynamics
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Parasites coinfecton
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Up to 10 species
Interspecific interactions Competition: negative, resources, direct interference, immune-mediated Facilitation: positive, immune trade-offs, suppression Determines host fitness, severity of symptoms, transmission of infection, success of control programs |
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Immune facilitation
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Parasites improve within-host environment for others via immunosuppression (worms)
Biasing host response: worms polarise towards Th2 response which reduces response to microparasites like malaria |
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Resource faciliation
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Parasites improve within-host environment for others by altering the composition of available resources
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Why study seabirds
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Cheap indicator, top predators, nesting sites, international obligation, media and public interest
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Seabird diet
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Small forage fish, middle of food chain, Sandeel: 3-10cm, difficult to monitor diet - most data from breeding season
Analyse via digestion of food samples and otolith bones give age and species, biomass of prey |
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Snake pipefish
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Invasive species, difficult to digest and handle, low nutritional value, related to seahorse, first recorded in 2004 but now almost absent
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Following seabird trends
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Easy to study birth/death rates as only need 1 population, rate of return estimates death
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Seabird breeding success
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Record sites where nests built, eggs laid, chicks fledged
Annual success = chicks fledged per nest built |
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Estimating adult seabird survival rate
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Catch and give unique tag, record sightings each season, estimate proportion alive corrected for proportion missed
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Determining how and where seabirds forage
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At-sea surveys, section into transect, density (all in transect), birds per unit distance (all birds in 180 degree scan)
Data loggers to legs or back, transmit or archive info, time activity budget, diving behaviour, summer and winter differences |
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Types of seabird foraging
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Surface feeding, dipping, shallow plunging, deep plunging, pursuit plunging, pursuit diving, aerial pursuit
0-250m below sea level |
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Seabirds daily energy expenditure
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Indirect calculation using bioenergetics modelling: time activity budget, consumption = DEE/assimilation efficiency (~70%)
Direct method of field metabolic measurement via heart rate monitor, doubly labelled water with elimination rate |
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Type of seabird most sensitive to change in prey abundance
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Small, short ranging, surface-feeding
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Wasp-waist food web
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Hourglass shaped, single/few species of small plankton-eating fish dominate
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Seabird faciliation
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Diving species make fish available to surface feeders
Small surface feeders opportunity small as larger individuals arrive and disrupt dynamic |
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Bottom-up fish web control
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Warmer oceans have copepod declines
Early northern species replaced by late southern Changes sandeel phenology Seabirds delay breeding so sandeels are available Mismatch index: eels change too fast |
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Top-down fish web control
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Herring control sandeel numbers
Catalysts create visual cues for other predators and suppressors break-up the whole scene |
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Human fish harvesting
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Increase pressure on white fish (cod, haddock) reduced numbers, fished down food chain to mackerel and herring, stocks down 90% in a few years from 1950, sandeels increased as they were competitors, partial recovery of whitefish
Sandeels fished when others depleted |
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Consequence of human fishing for seabirds
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Whitefish removal increased sandeels
Herring and mackerel reduced fish size without reducing population and declines caused increase in sandeels -0.39 kittiwake chicks/nest, no effect other species, surface feeders less other options |
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Epidemiology
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Study of infectious diseases in populations
Pathogenesis, transmission, demography, behaviour, host heterogeneity Prevention and control |
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Infectious diseases
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1/4 all deaths and morbidity
Malaria, AIDS, TB Epidemics |
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Emerging infectious disease
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Incidence is increasing following first introduction into defined host population or increasing as a result of long term changes
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HIV/AIDS
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Recognised early 1980s
>30m deaths, 33m current infections Jump from SIVcpz M pandemic |
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H5N1 Influenza A
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Poultry in 1959, bird reservoir?
First human case 1997, now >300 deaths Not transmissible between humans Cases show symptoms |
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SARS
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Coronavirus
2003 epidemic, spread via air travel Respiratory infection 800 deaths, 8000 cases Horseshoe bat reservoir? large colonies travel far |
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EBOLA virus
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Cause of haemorrhagic fever
>2000 cases, >60% mortality Blood-borne Human-human transmissible |
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NIPAH
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Malaysian pig farmer viral disease
100 cases, >70% fatality Fruit bat reservior |
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Monkeypox
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Relative of smallpox
Reduced immunity due to stopping of vaccination Direct contrat spreads 1-10% case fatality rate Pet-trade related outbreak in US |
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Zoonoses
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Diseases/infections naturally transmitted between humans and animals
60% of human pathogen species ~40% livestock pathogens, ~70% cat and dog |
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Disease reservoir
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1+ epidemiologically connected populations or environments in which the pathogen can be permanently maintained and from which infection can be transmitted to the defined target population
More important to share habitat than genes |
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Pathogen pyramid
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Exposure - infection - transmission - epidemic
Numbers reduce as go along chain |
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Drivers of pathogen emergence
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Human: society, demography, travel
Environment: agriculture, climate change, trade Pathogens: failure to control, evolution |
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Ways to identify and model drivers of pathogen emergence
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Describe, quantify and map, statistical and functional association with emergence, predict impact, drivers of drivers
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Ways to make maps of emerging infectious diseases caused by zoonotic pathogens
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Wildlife/zoonotic pathogens, non-wildlife/drug-resistant pathogens, vector-borne pathogens
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Calculating emerging infectious disease risk
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From regression coefficients and variable values
SD from the mean, mapped on linear scale |
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Fighting emerging pathogens
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Effective surveillance in potential reservoirs/internationally/wild animals/zoos
Multi-discipline: public and animal health agencies Biological and ecological drivers Public health screenings Health map web searches Detection - identification - monitoring |
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IOM Report
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Recommendations for future of infectious diseases
Technical: enable surveillance and response Economic: establish financing and incentives Political: coordinating body for global response |
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Community ecology
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Study of patterns in structure and behaviour of multispecies assemblages in a given time and place
Complex systems/patterns/processes |
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Community ecology questions
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How many species? Which species? Why do tropics differ from poles? Collapse after extinctions? Introduced species impact? Change over time? Disturbance influence?
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Community unit view
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Clements 1916/1936
Organised recurrent system of organisms, strong interactions, environment less important Common evolutionary history |
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Individual view
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Gleason 1926/1939
Local collection of populations, same environmental requirements and tolerances Loose boundaries, interactions weak/unimportant |
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Rank-abundance curve
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Common dominant species may drive structure
Rare species focus of conservation |
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Defining a community by species
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Impossible to consider all without a full sample
Higher taxa (birds,grasses), size, occupancy (resident, migrant) Miss some specific interactions; tropic, species focus Lacks generality |
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Ways to describe community structure
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Richness: number species
Dominance: greatest abundance/biomass Diversity: combines |
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Simpsons diversity index (D)
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1/Pi^2
Pi: number species/total number individuals |
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Shannon's index of diversity (H')
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- Pi ln Pi
Pi: number species/total number individuals Maximum = ln(S) |
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Evenness index
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Diversity higher if richness higher, more even distribution
Maximum diversity if all species are equally abundant D/Dmax = 1/Pi^2 x 1/S Most even = 1 |
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Alpha diversity
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Local diversity of a community calculated without reference to any others
Could have same diversity but totally different species |
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Beta diversity
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Between community/habitat/locality diversity
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Gamma diversity
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Regional diversity, number species across habitats/samples
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Community patterns in space and time
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Boundaries and gradients, soil/water/microclimates
Community unit: sharp boundaries Individualistic: continuum, diffused boundaries Resource partitioned continuum: mosiac |
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Influences on species coexistance
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Local: competition/predation come to equilibrium so fast that larger scale processes are unimportant
Regional: species distribution more important than co-occurance of species at any one point |
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What determines patterns of species diversity?
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Productivity, altitude, latitude, remoteness
Any factors which affect immigration, extinction, species, emmigration |
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Remoteness
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Island biogeography
Size/distance from each other and other islands Large/close island: immigration decreases as number of species increases Extinctions more likely on small island, rate of extinction increases as number of species increases Larger islands burn more freq from lightening wildfire |
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Latitude species gradients
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Most lizards/trees/butterflies at 0 latitude
Meta-analysis of 600 gradients Gradient steeper when richer taxa/larger organisms/marine/terrestrial/regional Steepness not influenced by dispersal/physiology/tropic level/hemisphere/range Combination of energy/climate/area processes Local scales within larger, oceans move energy via currents Tree richness increases as primary productivity increases |
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Disturbance and species richness
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Ideally 50%
Stops equilibrium and allows highest diversity Nutrients into system via cultivation, pollution High grazing increases richness in nutrient rich system Agriculture, livestock, disturbance |
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Factors affecting species richness
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Resource range, niche breadth, overlap, saturation, productivity
Interaction of factors Anything affecting speciation/extinction/immigration/emigration |
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Hypothetical explanations of species richness patterns
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Spatial/area: mid-domain, geographical area, species-energy, climate stability
Evolutionary: historical perturbation, evolutionary rate, effective evolutionary time Biotic |
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Studying soil
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CAT scan shows air space
Fluoresce active microbes Space and substrate in soil Heat transferred via water and conduction |
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Molecular techniques to study soil
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Phospholipid fatty acids
Fluorescence in situ hybridisation DGGE and T-RLF (DNA-based for fungi & bacteria) Microarrays |
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Biochar
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Stable carbon matrix
Can impact soil biodiversity and mediate key ecosystem services Charcoal, porous, provides niches |
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Community composition
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Patterns in space and time
Influence of energy input No input reduces abundance not diversity |
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Physiological response curve
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Response against function causing a response, e.g. elevation/temperature
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Distinct preference niches
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Functional fitness = physiological response curve = realised niche
Abundance = realised niche |
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Shared preference
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All species have the same optimum
Realised niche under the optimum for dominant/competitive species More tolerant driven into suboptimal niches Differentiation, resource partitioning, trade-off |
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Chronosequence
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Community pattern over time
Disturbance - gap - colonisation - replacement - succession How succession occurs in gap, how disturbance impacts dominance and abundance, spatial positions |
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Founder-controlled community
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Disturbance - gap - colonisation
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Dominance controlled community
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Disturbance - gap - colonisation - replacement - succession
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Rank-abundance curves
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Period of decades
Transition of species and abundance over time |
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Autogenic succession during raised bog formation
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Mud - phragmite fen mud - alnus fen - pinus/betula bog - carex/sphagnum bog - sphagnum bog
Invasion by trees is rare Dominant species affect their own environment |
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Transition of species types during succession
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Annual/high seed - perennial/vegetation colonisation - maximum life history diversity - perennial/colonal
Pioneer - mid - climax |
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Patch-dynamics
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Spatio-temporal context
How things change spatially over time |
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Metapopulation dynamics
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Local extinction/colonisation
Species persist even if extinct in an area Spatial movement, mixing |
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Lottery models
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Local extinction/colonisation probable
Dispersal/migration between patches Mosiac Stable equilibrium if equal competitors |
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Competition
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Reduces fecundity, reproduction, survival
Intra/interspecific, interference, exploitation, apparent dN/dt = rN(K-N)/K r = intrinsic growth rate alpha = measures effect of competition Less important in natural communities Abiotic factors more important in driving fluctuations, 40-95% temporal variance |
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Utilisation functions
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Ability to exploit a resource as it varies along a niche axis
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Coexistance
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If interspecific competition is lower than intraspecific
Very similar niches have low exclusion Aggregated distributions reduce competition Spatial heterogeneity Temporal variation Anything reducing density, e.g. predation |
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Tilman's R*
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Minimum resource concentration for a species to maintain population size
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Generalist predator
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Keeps dominant species in check, consumes most abundant, allows high diversity: predator mediated coexistance
Rabbits keep high plant diversity with no dominance, without had tall grasses then taller self-shading |
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Selective predator
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Narrow feeding niche
Pisaster starfish: 12 prey items reduce to 8 without it, keystone species, not most abundant but great impact, not dominant, recognised via removal |
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Main community structuring processes
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Equilibrium: competition, predation, mutualism, resource limitation
Non-equilibrium: disturbance, environment forcing, spatial heterogeneity, opportunism, dispersal |
