bio ecology

ecology

the relationship between organisms, their biotic and abiotic environment, and humans

one view of ecology

people separate from organisms and their environment, industrial capitalism and colonialism

ecology

the relationship between organisms, their biotic and abiotic environment, and humans

one view of ecology

people separate from organisms and their environment, industrial capitalism and colonialism

another view of ecology

people, organisms, environment all related

biomes and climate

biomes depend approximately on climate

temperature increases at low latitudes

because they receive more solar radiation

precipitation decreases at mid-latitudes

because of hadley cell air circulation patterns

temperature decreases at higher elevation

rising air expands and cools, falling air compresses and warms, lapse rate: every 1000 m elevation increase causes a 5-10 degree C decrease (depends on moisture and other phenomena)

precipitation increases at high elevation on westward side of mountains

west (windward side) : cool air flow, precipitation at high elevation

east: rain shadow, leeward side of mountains

earth’s tilt and seasons

the earth’s tilt causes seasons

oceans buffer climate

water warms and cools quickly, so climate extremes are stronger in the interior continents

effects of elevation/latitude on biome are similar

rainfall wet at equator, dry at 30, wet at 40-60, temp seasonality greater at higher latitude and less near ocean

climate

long-term weather patterns

biome

combinations of climate and species with similar ranges

temperature

expresses quantitatively the perceptions of hotness and coldness

precipitation

condensation of water vapor from the atmosphere due to gravitational pull of clouds

elevation

height above or below a fixed reference point

latitude

coordinate that specifies north south position of a point on the surface of the earth

maritime climate

occurs in regions where climatic characteristics are conditioned by their position close to a sea or ocean

continental climate

middle latitudes, temperatures not moderated by oceans

hadley cell

low latitude overturning circulations that have air rising at the equator and air sinking at roughly 30 latitude

mediterranean climate

hot, dry summers and cool, wet winters, located between 30 and 45, western sides of continents

species distributions overlap within biomes

geographic distributions (ranges) vary across species

what sets limits to species distribution

all occur simultaneously: can species disperse to a location, are the abiotic and biotic environment suitable for the suitable for the survival, growth, and reproduction of the species

humans can influence or shift any of these limits, behavior can influence any of these limits

dispersal

the movement of individuals or gametes away from (& potentially back to) their original location

dispersal via several mechanisms

animal vector (ingested/excreted), mobile, wind, water, animal vector (exterior)

dispersal often limits species distributions

dispersal event increases species range, demonstrates that distributions were limited by dispersal rates, and NOT by environmental limits

abiotic

non-living components

biotic

living components of the environment, some parts of the environment, such as soil and natural waters blend of both

biotic factors

can influence dispersal, can influence abiotic limits

species limits are partially set by geographic distribution of abiotic and biotic gradients

temperature, elevation, storm risk, predation risk

types of gradients

physically continuous: ex. gradient in temp moving from bottom to top of a mountain

patchy: range of environmental conditions

species distributions along gradients

species often occur where performance is highest along an environmental gradient, species distributions are often limited at one end of the range by abiotic environmental factors and at the other end by biotic environmental factors

measuring species presence and diversity to access stream health

presence of one or many bioindicator species at a site can tell us about environmental conditions there

assuming dispersal or biotic environment do not affect distributions, can assume water quality

environment

the surroundings and conditions in which an organism operates

behavior

the way in which an animal or human reacts to a particular situation

environmental gradient

change in abiotic factors over time

indicator species

an organisms whose presence, absence or abundance, reflects the specific environmental condition

biodiversity

spatial scale, set of organisms, what do you mean by diversity

scales of diversity

spatial grain: the characteristic at which measurements are reported

spatial extent: the overall region in which the measurements are made at the selected spatial grain (ex. entire state)

diversity metrics

abundance - number of species (total or per species), richness - total number of species, evenness - relative similarity in abundance of species, composition - identities of which species are present (think of individuals as diff m & ms, diff species are diff colors, bowl = scale of measurment)

counting number of species

we can stack species range maps like pancakes and count species richness at each location (same grain) within the overall extent of interest

latitudinal diversity gradient (LDG)

pattern of changes in species richness with latitude, generally highest species richness near the equator, observed to exist across taxonomic groups

leading explanations for the LDG

environments are less stressful in the tropics meaning more species can survive (warmer/wetter), more energy available in the tropics meaning more ways to differentiate niches/ support more species, higher temperatures in the tropics biochemically drive higher mutation rates and thus speciation rates, more competition in the tropics more net speciation, more time to evolve new species in the tropics (no ice sheets), more land area supports more species in the tropics

ldg in the past

absent , diversity peaks at latitudes with greater land area

biomes found in different locations in the past

antartica had warm forests, warm temps around 20, no ice sheets, atmospheric co2 concentrations higher, forests in complete darkness during long polar winters

larger area

higher richness

island biogeography

islands closer to mainland get more immigration of species than farther islands, larger islands have lower extinction rates (more ways for species to survive)

equilibrium richness on island

determined by the balance between immigration and extinction, and thus by island size and distance from mainland

longer time since disturbance

higher richness, tree richness also higher in wetter environments, general trend for plants too

more agricultural intensification

lower arthopod richness

more land clearance

lower abundance and richness

agroforestry systems

can maintain higher biodiversity than intensive/ plantation agriculture

argoforestry

(practices involving maintaining natural landscape fragments, intermixing species being cultivated, etc), preserve traditional knowledge and cultural practices

more indigenous land use

higher richness of culturally important plants, ade: amazonian dark earth, a type of nutrient-rich soil thought to have been created through intensive land use and fertilization by indigenous peoples of the amazon, more ade higher richness of edible plants

less poverty

higher species richness in cities

population

a group of individuals of a single species in a certain area, may interact with each other, area be quite diffuse if the organisms are mobile

species distributions/ range limits often emerge from population growth rate variation across space

a species is absent in a location when an extent population cannot persist (due to all (dispersal, biotic, and abiotic environmental factors)

if dispersal is not limiting, the range limit is set by where zero or negative population growth rates occur

populations can grow or shrink over time

demography

the study of the vital statistics of a population and how they change over time

births, deaths, immigration, emigration

bide model

Nt+1 = Nt + B + I - D - E

Nt

the number of individuals in a population at time t (time interval usually one year for plants and animals but depends on the population we are studying)

B

the number of births in the next time interval

I

the number of immigrants in the next time interval

D

the number of deaths in the next time interval

E

the number of emigrants in the next time interval

Nt+1 = Nt + B - D

the size of a population in a given year is the size in the previous year plus the number of new individuals born and minus the number of individuals that died

geometric growth

assume B-D is a constant fraction - change r of Nt

B-D/ Nt = change r - means each individual’s birth and death probability is constant and does not change over time Nt + 1 = Nt + change r (Nt)

Nt+1 Nt = change N / change over time = change r (Nt)

when to use exponential model

reproduction happen continuously, continuous, N0 x e^rt, a population of bacteria that reproduce at any time

when to use geometric model

reproduction happen at discrete times, discrete, Nt = (1+ change r) ^t x N0, a population of annal plants that reproduce once every winter

can exponential or geometrical growth continue forever

eventually our assumption that “each individual, on average has a rate of reproduction in the population equal to r regardless of the size of the population” breaks down, growth slows down as populations become bigger, need more complex model to describe reality

thomas malthus

argues population ultimately will be kept in check either by increases in death rate (war, conflict) or decreases in birth rate (gov policy, eugenics, sterilization)

evidence on a graph of N vs t that indicates that an exponential or geometric model is NOT a good description of the system

decrease in population, line would not be linear when y is logged, mass immediately extinctions, rate of change changes from year to year so the graph fluctuates up and down, population plateau

exponential growth cannot continue forever

populations can become limited as they grow

eventual equilibrium reached

per capita population growth rate

1/N (dN/dt) rate of population growth divided by population size

a metric of the average rate of population change for an average individual in the population

density dependence

changes in per-capita population growth rate with population size

negative density dependence means that per-capita population growth rate decreases when the population is larger - a necessary condition for a population to stop growing

a population comes to equilibrium when 1/N (dN/dt) = 0

typically, birth rates show negative density dependence and death rates show positive density independence

equilibrium reached when b = d

why is negative density dependence common

life usually becomes more challenging in denser populations, reducing birth rates and increasing death rates, fewer resources per individual (if total resource pool is fixed), more competition among individuals, fewer available mates, more disease and parasites, more predation risk (easier to be hunted when common)

no density dependence in exponential growth model

growth rate of population calculated on a per-individual basis, no density dependence

adding negative density to the exponential model

deriving the logistic model

1/N dN/dt = r (1 - N/K) r = constant value as in exponential model, 1 - N/K line with negative slope (new in logistic model)

properties of the logistic model

r = intrinsic growth rate, constant number, describes how quickly population size will increase starting at very low density, ‘intrinsic’ in relation to the species biology and the environmental context

K

carrying capacity, a constant number, population size at which N comes to equilibrium

per capita growth rate is highest when the population is small, and is small, and is identical to in the exponential model

population comes to equilibrium when N = K

logistic growth

S shape, carrying capacity

dN/ dt

rate of population growth in time ^-1

1/N * dN/dt

per capita rate of population growth in time ^-1

r

intrinsic growth rate in time ^-1

K

carrying capacity

density dependence

when the per capita rate of population growth varies with N

density independent factors can influence the population size at which births equal deaths

dN/dt at any instant is limited by something unrelated to the size of the population

external environment aspects: cold winters, droughts, storms, volcanic eruptions

populations display erratic growth patterns because density independent factors change over time

density independent factors can increase or decrease parameters like r and K over time, though we often cannot measure effects directly

examples of density independent factors

affecting k

changes in temperature, changes in moisture availability, changes in land area

examples of density independent factors

affecting r

changes in temperature, changes in moisture availability, change in allele frequencies

most populations do not actually display exponential or logistic growth

population fluctuations are common

density independent factors that vary over time, variation in immigration and emigration

populations collapse can sometimes occur

common misconception: collapse always occurs if a population temporarily exceeds carrying capacity - smaller fluctuations are most likely in most scenarios

life histories are linked to population growth

life history: suite of traits related to a species’ life cycle and the timing of major events

ex. age at first reproduction, average lifespan

life histories vary across species

principle of allocation

individual organisms have limited amount of resources to invest in different activities and functions, resources invested in one function are not available for another (trade-off)

in life cycle, resources must be allocated among growth, survival and reproduction

reproduction size-number tradeoffs

species can have smaller or fewer bigger offspring

costs of reproduction

more reproduction in one year means less reproduction the next year

some life-history traits are coordinated along a “fast-slow cntinuum”

fast-slow continuum explains about 35% of the life history trait variation we see across organisms

fast: few reproductions per lifetime but many per reproductive episode, no parental care, small offspring or eggs vs slow: many number of reproductions but few per reproductive episode, often extensive parental care, large offspring or eggs