Biodiversity, Ecology and Conservation Flashcards
Definition of ecology
Interaction between organisms (biotic) and their environment (biotic and abiotic)
Definition of biological species
Two organisms which cannot breed to produce viable, fertile offspring
Definition of population
A group of individuals of 1 species living and interacting in one area at a given time
Definition of community
Associations of populations of 2 or more different species in the same area
Definition of ecosystems
Community and physical environment and the transfer between different trophic levels in the whole environment
Definition of landscapes
Areas with considerable differences e.g. multiple ecosystems
Definition of biosphere
All the world’s ecosystems i.e. all living organisms and their environment
Definition of assemblages
A group of similar animals e.g. an assemblage of birds
Definition of population dynamics
How population size varies through time
Basic population equation and what it is used to calculate
Nt+1 = Nt + B - D + I - E
To calculate population size for animals with annual breeding cycles
Definition of geometric growth
Species population changes in size by a constant proportion in discrete time steps
Definition of exponential growth
Species population with continuous reproduction changes in size by a constant proportion at each instant in time
When does unlimited population growth occur?
- no competition and unlimited resources
- in small populations
- Newly colonised regions
- e.g. Muskox, Alaska
Important population measures
- Population size i.e. number of individuals
2. Population density i.e. number of individuals/ area or vol
What are area-based counts
Count sessile individuals or vegetation using quadrats or aerial surveys for large mammals in a known area
What are distance-based counts
Measure distances individuals seen from a transect line/ point to estimate relative number of individuals/ unit area
Definition of relative population size
Number of individuals in time/ place relative to a number in another
Methods used to measure population sizes
- Area-based counts
- Distance-based counts
- Capture, mark, release, recapture
Capture, mark, release, recapture equation to estimate population size
Total population (N) = (Number marked first catch (M) x total caught second catch (C) / number marked second catch (R) N = (M x C)/R
Assumptions and issues with capture, mark, release, recapture
- No B, D, I or E between M and R i.e. equal chance of capture
- No harm during process
- Marks do not fade
- Overestimate if animals learn to avoid recapture
- Underestimate if animals get preferentially caught
Definition of intraspecific competition
Competition within members of the same species as similar resource requirements i.e. demand>supply
Definition of interspecific competition
Competition between different species where both suffer negatively
Definition of carrying capacity (K)
The upper sustainable limit of a population
Begon et al. (1996) intraspecific comp. characteristics
- Effect is a measurable reduction in an individual’s contribution to future generations
e. g. a) fecundity (Cain 2011) - song sparrow breeding pairs and offpsring survival b) survivorship (van Balen 1980) - supplementary feeding and great tit breeding pairs - Resources must be in limited supply
- Reciprocity e.g. bird of prey chicks, spadefoot toad phenotypic plasticity
- Density dependent e.g. Tribolium confusum, soybean survivorship
Population growth models
- Exponential growth equation
2. Discrete logistic growth equation
Exponential growth equation
Nt+1 = reproductive rate x Nt
Nt = pop. size
Discrete logistic growth equation
Represents intraspecific competition
Nt+1 = reproduction rate x Nt (1 - Nt/K)
- calculate N at different time phrases
- plot Nt (y) against time (x) to see population growth
Characteristics of density dependence
- closely linked to intraspecific competition
- regulates population sizes around an optimum K value
Population regulation
- Regulating equilibrium around K by DD factor regulation (pop. often fluctuates)
- DD factors do not regulate if there is a time delay or if it only regulates in certain environmental conditions
- Different factors, e.g. food, waste, predation, may cause DD
What is cobwebbing (Ricker-Moran plots), how to use them and features?
Graphical method to predict the results of intraspecific competition and show population dynamics
- plot curve represented by the discrete logistic growth equation
- plot straight line to present unchanging population around K
- plot graph N against time
Changes to curve shape can majorly impact population stability and dynamics
Patterns vary i.e. cycles, oscillations, fluctuations
Ricker-Moran plot pattern examples
- Yeast rises smoothly with no fluctuation around K
- Callosobruchus beetles have a decreasing oscillating pattern
- Tasmanian sheep show regular fluctuations
- Great Tits have no order and wide fluctuations
Definition of mutualism
Both species benefit i.e. symbiotic e.g. zebra and oxpecker
Definition of commensalism
Presence of one species needed for another e.g. crabs and species living in their shells
Definition of predation
One species usually kills another
Definition of ammensalism
One species has a negative effect on another but it itself is unaffected e.g. elephants walking through vegetation
Types of interspecific competition
- Exploitation (indirect)
2. Interference (direct)
Definition of competitive exclusion
One species may have a competitive advantage over another resulting in one becoming out-competed (exploitation competition) and extinct
Example of competitive exclusion
- (Park 1948) flour beetles:
a) abiotic: T. castaneum wins 100% in hot-moist climate whilst T. confusum wins 90% in hot dry
b) biotic: confusum competitive advantage in presence of parasites - (Tansley) Galium species:
G. sylvestre outcompetes on limestone and G. saxatile on peat
Definition of niche theory
Ultimate distribution unit related to species’ ecological position
Types of niche
- Fundamental
2. Realised
Definition of niche partitioning
Alter and shift niche to reduce overlap and enable co-existence by avoiding/ reducing interspecific competition
e.g. (Gause) grown together P. caudatum ate bacteria on surface and P. bursaria ate settled bacteria
Niche partitioning mechanisms
- Resource Partitioning
2. Character displacement
Resource Partitioning
- Change niche components
- Reduce interspecific competition by narrowing niches
- May increase intraspecific competition
- e.g. (Schoener) 4 species of Anolis lizard live and eat similar food but height and thickness of perch and time spent in sun/shade differ
Character displacement
- Changing morphologically
- long term evolutionary response
- e.g. Hydrobia snails usually 3.5mm but together H. ulvae = 4mm and H. ventrosa = 3mm
- e.g. Geospiza finch beak size. G. fulignosa smaller than G. fortis
Brown and Davidson (1977) niche partitioning experiment
- exploitative competition between seed-eating ants and rodents
- ant colonies increase by 70% when rodents removed and rodents increase by 18% when ants removed
- interspecific competition - remove both seed density increases from 1 to 5.5
- interference competition - rodents enter ant burrows whilst ants sting rodents
- resource partitioning between ant species
- character displacement of ant foraging strategies
What are mortality/ survivorship curves?
Graphical representation of survivorship from life tables
Pearl (1928)’s survivorship curve types
- Low early, high late mortality e.g. humans, mountain sheep
- Constant probability e.g. passerines
- Very high early mortality but high survivorship if survive e.g. fish, LEDC humans (30% Gambians)
What are cohorts and life tables used for?
To study population trends and predict population sizes
Definition of cohort
Group of animals born in the same time interval. Track fate from birth to death for population information
Function of life tables
Provide information about birth and death patterns and summarise variations in survival and reproductive rates with age
Types of life tables
- Diagrammatic
2. Cohort
Diagrammatic life tables
- easy to follow
- harder to analyse and make predictions
- e.g. Great Tits have overlapping generations so individuals alive at t+1 = range of ages
Cohort life tables
- more reliable
- for continuously breeding or overlapping generations
- change in mortality with age/ stage
- construct fecundity schedules by measuring births at different ages
- plants, sessile organisms, animals with annual life-cycles
k-values (“killing power”)
- reflect intensity/ mortality rate at each stage relative to the next as sequential mortality factors
- scaled and standardised
- sum to show overall mortality
What is the key factor?
The most important k factor.
Correlates most closely with k-total and contributes most to overall mortality
What is the regulating factor?
k factor which correlates most closely is the main population regulator
Compare k-values with population size by plotting each k value separately against measure of population size over years
Types of life tables
- Fixed - look at a pop. cohort. Usually simple annual cycles
- Static - study whole pop. in a single year. Usually highly mobile/ cryptic species e.g. Red Deer on Isle of Rhum
Lowe 1969 static life table of Red Deer on Isle of Rhum
- reconstructed pop. age structure of 1957
- smoothed the data
- survivorship reduced with age
- High mortality at 8-10 years after high birth rate
Definition of true predators
Complete consumption of another species
Definition of parasites
Rarely kill host but effects vary. Obligate association with host (co-evolution)
e.g. pathogen, Myxoma virus
Definition of parasitoids
Kill host by laying eggs which hatch and eat host from within
Definition of hyperparasitoid
Parasitise on another parasite/ parasitoid
Definition of herbivores
Eat tissue/ internal fluids of living plants/ algae
Plant defences
- Chemical
- Mechanical
- Nutritional
- Tolerance
Predator-prey relationships
- Delayed DD coupled oscillations e.g. hare and lynx
- no link/ relationship e.g. woodmice and tawny owl
- Prey outbreaks
Hare population cycle
Krebs et al. 1995
- interaction between food and predator
- remove predator, hares increase x2
- add food, hares increase x3
- both, hares increase x10 but density still decline
Definition of monophagous
Single prey species/ genera therefore may have coupled oscillations
Definition of oligophagous
Few prey types
Definition of polyphagous
Many prey species
Evolutionary predator adaptations
- Physical e.g. speed
- Poison
- Detoxification/ chemical tolerance
Evolutionary prey adaptations
- Physical e.g. body forms
- Armour
- Behaviour
- Mimicry
Characteristics of specialist predators
Shorter search than handling time
Characteristics of generalist predators
Longer search than handling time
Predator switching
Predators may become specialist if they show a preference
Efficiency may increase with reliable search images
Ecological impacts of parasites
- Increase diversity if attack dominant competitor
- Reduce distribution range
- Near host extinctions
- Affect population dynamics
- Change physical environment
Community level interactions
- Direct i.e. between 2 species
2. Indirect i.e. relationship between 2 species is mediated by a 3rd (or more)
Definition of trophic cascade
Consumption at one trophic level causes change in abundance composition at lower trophic level and can affect whole ecosystem
Definition of trophic facilitation
Direct positive interaction between consumer’s prey and another species which indirectly facilitates the consumer
Definition of competitive hierarchy
Linear relationship as no feedback with a dominating species i.e. A -> B -> C
Definition of competitive network
Circular relationship between species as every species has a negative impact on another resulting in stability and co-existance as no single species dominates
Definition of keystone species
Relatively rare but disproportionally large impact on ecosystem
Definition of ecological dominants
Species which have large impacts due to high abundance
Disturbance
- can reduce population sizes so resources become non-limiting affecting species richness
- varies in intensity and frequency
- creates gaps allowing colonisation and creates a mosaic community
Intermediate disturbance hypothesis
Connell
- low disturbance/ climax community = low diversity as competitive exclusion via dominant species
- highest species richness at intermediate levels i.e. mid-succession
- high disturbance = low species richness as high mortality
- e.g. Sousa algal communities on rocky shores
Definition of biodiversity
The variability among living organisms: within species, between species and of ecosystems
Why conservation science important?
- Threatened species rising i.e. now 24,307
- Varies taxanomically e.g. 64% Cycadopsida threatened
- Extinction rates higher than normal background rates e.g. amphibians 66 to 107, 5 mass extinctions
- Dominant biodiversity loss drivers vary geographically (Sala)
When did the Anthropocene begin?
a) 1610 as CO2 concentrations began to rise
b) 1964 - radioactivity peaks
Biggest threat to mammals
Overexploitation with >6000 species affected
What is Conservation Biology?
- Soule 1985
- address biodiversity and nature issues caused by humans
- crisis biology i.e. act now, data later
- intrinsic value of biodiversity i.e. protection for itself
Conservation Biology value statements
- High organism diversity is good
- Extinction is bad
- Ecological complexity is good
- Evolution and genetic diversity is good
Conservation Biology Tools
- Singe large or several small (SLOSS), Simberloff and Abele, 1982
- Minimum Viable Population (MVP), Schaffer 1981
- Convention on International Trade in Endangered Species (CITES), 1975
What is Minimum Viable Population (MVP)?
Smallest number of individuals needed for an isolated population to persist at a preferred probability (90-95%) for a predefined time into the future (100 years)
What is CITES?
- international agreement between 183 governments
- regulates trade
- 3 appendices covering 5800 animals and 30,000 plants:
1. Cannot trade unless exceptional circumstances
2. Regulate trade to prevent worsening already threatened status
3. Between 2 countries. May be threatened in a particular country but not globally so may want to regulate trade
What is Conservation Science?
- Kareiva and Marvier, 2012
- coupled human - natural systems
- maximise benefits for nature and humans
- systematic data collection
- CB + human consideration
- instrumental value of biodiversity i.e. it also helps achieve other things
Conservation Science value statements
- Human well-being is important
- Maximise human and biodiversity benefits
- Evidence-based and community involvement
- Pristine nature does not exist
- Avoid ‘tragedy of the commons’
- Local and global conservation linked
How has conservation context changed 1985 vs 2012
- 40 % human population increase = increased demand
- CO2 increase and climate change
- More protection e.g. marine <1mil km2 to >8.1 mil
- Culture change
- Purpose has changed (Mace) i.e. 1960-70 = nature itself whilst now = people + nature
Conservation policies
- Convention on Biological Diversity (CBD)
- Strategic Plan for Biodiversity
- 17 Sustainable Development Goals
What is CBD?
- UN policy
- Following 1992 Rio Earth summit
- 2010 targets to reduce rate of biodiversity loss not met
What is the Strategic Plan for Biodiversity?
- 2011-2020
- 5 strategic goals each with 20 targets
- mostly insufficient/ no progress
What are the Sustainable Development Goals?
- UN
- broad blueprint for a more sustainable future
- reviewed annually
- meet by 2030
- more research linked
Conservation success examples
- Southern White Rhino went extinct in 1800s but rediscovered and NT in 2008. Following translocation and restocking now > 20,000
- Golden Lion Tamarain went from CE, 1996 to EN, 2003. Translocation and now around 1000 with 1/3 from captive stocks
- 68 status improvements
IUCN Databases
- ECOLEX
- Protected Plants
- Key Biodiversity Areas
- Red List of Ecosystems
- Red List of Threatened Species (1964)
IUCN species Red List criteria
- Population decline measured using counts, demographic data, presence/ absence
- Geographic Range Size i.e. spatial distribution in areas of known presence.
- Fragmentation
- Small Population Size - MVP, extinction vortex
- extinction risk assessed based either on decline rate over time or just point based
What is Population Viability Analysis (PVA)?
- Gilpin and Soule, 1986
- determine viability and extinction for particular time and environment
1. Time-series i.e. use estimates of total number to define average growth trend and variance
2. Demographic - use estimates of age/ stage specific vital rates
3. Individual based models and patch- occupancy data