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• Ecology: the study of – Drivers of biodiversity – Drivers of a species’ distribution – Drivers of a species’ abundance • Environmental science: – The study of the impact of humans on the BIO 225: ACT III environment – Emphasis on air and water quality • Conservation Biology: Ecology – The study of imperiled species and habitats • Animal Rights, Environmentalism, Plant Rights

• People were doing ecology before there was Ecology ecology • Understanding the abundance of organisms • Aristotle Historia Animalium and their distributions is how our species – Descriptions of animals and plants survives! – Described plagues and the environment as a control • Comes from “oekologie” coined by German • Greek physician, Pedanios Dioscorides (active AD scientist Ernst Haeckel (oikos = house) 60s–70s) – De Materia Medica • Became ecology in 1893 – Identification and natural history of medically important plants • Romans – More practical: wrote on agriculture

Ecology: Post-Classic to Pre-Enlightenment Ecology: Demographics

• Mostly descriptive • Many early scientists were interested in estimating human populations • Study of plants was mostly related to medicine and trends • Andreas Vesalius’ De fabrica humanis (1543) • John Graunt (1620–1674), who also held several city offices, published – One of the first books showing dissected humans and animals Natural and Political Observations Mentioned in a following Index, and Made upon the Bills of Mortality: with Reference to the Government, • Conrad Gessner (Swiss) 1555 Historiae animalium Religion, Trade, Growth, Ayre, Diseases, and the several Changes of the – Wrote on the natural history of animals said City.

– Outlined the important aspects of demography: births, deaths, sex ratios, age structure – Referred to wild animals

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Geography Ecology: the small stuff • Alexander von Humboldt (1769–1859) • I shall try to find out how the forces of nature interact • Robert Hooke (1635–1703) upon one another and how the geographic environment influences plant and animal life. In other • Micrographia words, I must find out about the unity of nature – Plant cells, microorganisms • World traveler • Noted the relationship between climate and the limits • Inventor of distributions • Inspired Darwin (and many others) – barometer, thermometer, hygroscope, rain gauge, and wind gauge

Enter Darwin Population Biology

• Natural selection • Essential to understand human populations • Phylogeography • Essential to understand endangered species • Climate • Essential to understand pests • Pollination • Essential to understand other economically • Earthworms important species • Dispersal

Defining the individual Terms

• Unitary • Distribution – Individuals are discrete • Range – Less plasticity • Territory • Modular • Abundance – Individuals reproduce by modules – More plasticity • Density – Ramets and genets • Population – Biomass • Metapopulations • Growth • Dispersion – Determinate • mammals, some plants [mostly herbs])\ • Dispersal – Indeterminate • Reptiles, most plants

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Biogeography Plate Tectonics

• Why are organisms found in some areas and • http://www.tectonics.caltech.edu/outreach/a not in others? nimations/anim_pangaea/Resources/anim_pa – Organisms have histories ngaea.mov – Organisms vary in their ability to disperse – Organisms vary in their environmental tolerances

Species level: Helmeted Hornbill Family level: Hornbills

Order level: Coraciiformes Habitat suitability

• Abiotic factors

– Temperature, precip, pH, O2, salinity • Biotic factors – Predators, prey, parasites, disease, competitors • Abiotic x biotic

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Density and Dispersion

Densities vary across range

• Breeding bird survey maps • In general, species reach their highest densities in the center of the range

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Spatial Resolution and Distributions Populations (see Fig 8.15) • Number of individuals – All individuals (N) – Sample (n) – Within a natural boundary • Islands • Well defined habitats (e.g., pond) – Within an arbitrary boundary • State, region, county

Populations Population Indices

• Population Index – Not all organisms are counted – Some standard is chosen then changes indicate Snowdonia hawkweed from the beautiful N is very rarely ever known nation of Wales. N=1 population changes • except for the very rare! – Common in wildlife management • or very obvious in well- – Example defined boundaries • deer brought into check stations indicate the •too rare? extinct? population when the number of deer out there are

never known

Population Indices Population Estimation • Population Indices – Minimal work (therefore cheap) • Population estimation attempts to figure out how many – Minimal information individuals there are in an area • Difficult to predict the consequences of management decisions – N can refer to all individuals of a species but more often the total • Adaptive management number of individuals in an area • Difficult to predict the consequences of environmental changes – A sample of a population is n and can be used to estimate N – Climate change – Formally, n = N ˆ (N hat) – Introduced species (parasites, disease [West Nile], new food, – N is hardly ever known predators, competitors) – A good estimate is when Nˆ  N

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Population Estimates Capture-Recapture

• How do we get N ˆ ? • Animals are captured, marked, released, and • Plants then resampled • – Sample in a small area to get density then Labor intensive (not cheap) extrapolate • Lots of assumptions – Density = number of individuals/area – Animals don’t avoid trapping – • Animals Many more but… • Lots of information – Capture-recapture – Survivorship, sex ratios, recruitment, health, DNA samples, etc

Capture – Recapture Capture – recapture

• Many animals are PIT tagged • 2 sample – Passive Integrated Transponder (n )(n 1) (n )(n 1)(n  recaptured – used in livestock and pets as well as wildlife Nˆ  initial second  initial second second recaptured 1 (recaptured 1)2 (recaptured  2) • Mammals get ear tagged • Birds get banded • Animals with complex patterns can be photographed – Whales, jaguars, some salamanders • Insects and hummingbirds – white out!

Spatial Scale: Extent Spatial Scale: Resolution

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Geographic Range Population Growth and Regulation

• Examples – Giant puffball • produces 7 trillion spores/individual • If all lived and each produced 7 trillion spores each • The mass of puffballs = mass of Earth – European Starling • 1890 ~ 160 released in Central Park, presently 170 million – African Elephant • 1 pair will become 19 million in 700 years

Life table analysis Vital rates and life tables

• Types • Closed population – Cohort/Longitudinal – Birth, death, sex ratios, age structure • Organisms (including people) are followed from start to • Open Population finish • Difficult in long-lived organisms – Closed population vital rates + emigration and • Important in epidemiology immigration – Static • Vital rates are estimated from life table analysis • Organisms of all ages are studied at once • Life tables • Vital rates (births and deaths) are assumed to be constant – Cohort (longitudinal) – Static (cross sectional)

Life Table Elements of a life table

• Requires • Survival rate (Sx): – Age or stage – probability of surviving to the next age/stage – Number of births for each age or stage (Nx+1/Nx)

– Number alive at each age or stage • Survivorship (lx) : • You calculate – proportion of original cohort surviving to time x – EVERYTHING! (Nx/N0) – Survival rates and fecundity rates

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Elements of a life table extended Life Table

• Life expectancy

– Lx = (lx + lx+1)/2 – Tx = SUM(Lx)*Age span for category x • Death rate (dx) = lx - lx+1 • Age specific mortality rate (qx) = dx/lx • mx = Fx/nx • Age specific fecundity rate fx = mxlx • Basic reproductive rate R0 = SUM mxlx

Life Table Basic Reproductive Rate

Survivorship Curves Fecundity

• Semelparous • Iteroparity – Iteroparity and age – Iteroparity and size – Iteroparity and resources

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Fecundity and age Age class and sex ratios

Lambda and r Population Growth

• Both refer to growth rates • Note the direction and shape of the curves • Use λ when reproduction is pulsed/seasonal • Pulsed breeding N   t1 – Changing starting population N • Use r when reproductiont in continuous – Changing lambda dN • Continuous breeding r  dt – Changing starting population N – Changing r • Note that   e r or r=?

Doubling time So far no stopping populations

• Is the time it takes for a population to double • Our models have populations increasing to ln 2 infinity (and beyond) t  d r • Realistic?

• Human population growth rate is 1.18%. What is the doubling time?

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Population Regulation Carrying capacity

• Limiting factor • Maximum population a habitat can sustain – The resource that, if increased, would result in a population increase • Represented with K • Density-independent factors – Climate • In rare cases, K is a constant • Density-dependent factors – Breeding site limitation – Disease – Space availability for sessile organisms – Food – Competition • More likely that K changes over time • Mates • Resources • Breeding sites

Fecundity and Density Population growth

t Nt   N0

rt Nt  N0e

Logistic Growth Logistic Growth

• Growth rates dN  K  N   rN  dt  K 

K Nt  • Population size  K  N0  rt 1  e  N0 

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Logistic Growth Human Populations

Human Populations

• 7 billion • http://www.census.gov/main/www/popclock. html

Population Dynamics

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Population Dynamics Mallards in North America

• Populations differ in their dynamics over time – Some populations are relatively stable – Some populations vary – Some populations are highly variable

Role of competition in phytoplankton population for the occurrence and control of plankton bloom in the presence of environmental fluctuations. Ecological Modeling. Greater Prairie Chicken

Rodent and predator population dynamics in an eruptive system. Ecological Modeling. 142. Delayed Density Dependence

• Fig 10.10

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Predator-prey oscillations Extinctions

• Figure 10.9 • Small populations at greater risk of extinction – Inbreeding – Demographic stochasticity – Environmental stochasticity – Castastrophes – Allee effect

Extinction-Colonization Habitat Fragmentation

• On the smallest scale, individuals die and • Patchiness of habitat is normal offspring may take their place • Metapopulations are sustained by dispersal • Small populations in habitat patches may go • If dispersal to patches is reduced then local extinct extinction will occur • The patch can be recolonized through • Habitat fragmentation reduces dispersal dispersal • These subpopulations are called metapopulations

Habitat Fragmentation Habitat Fragmentation

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