declining population paradigm (lecture 6) Flashcards
What are the differences between the small and declining population paradigms?
- continuum, relative importance of factors shift over time
small population (SP):
- rich in theory
- promotes local & very intensive management
- firefighting
e. g. vaquita: < 30 individuals
declining population (DP):
- less rich in theory
- general principles concerning diagnosis and management of causes of decline
- less intensive management over larger areas
- proactive
What is an example of the declining population paradigm affecting small populations?
Spoon-billed sandpiper (CE)
- previously 3000 pairs now <200
- low breeding successes: disturbance and predation
- large scale winter habitat loss
- low recruitment: hunting
i.e. not yet experiencing stochasticity, inbreeding, allee effects
How can small and declining population paradigms act together?
- Atitilan grebe
factors driving decline change over time:
- DPP: habitat destruction, exotic species
- SPP: earthquake, hybridisation
- multiple factors interact (can be synergistic)
- diagnosing & thus reversing causes of decline is essential, but difficult
What are difficulties with declining populations discovery?
- difficult due to geographic or taxonomic biases in monitoring
- many species are data deficient
- need to exploit other methods
How are declining populations discovered?
- naturalist recordings
- haphazard naturalists’ recordings can reveal past population sizes/population crashes
How are declining populations discovered?
- local people
- interviewing local people e.g. fisherman can give accurate idea of population declines if shifting baselines taken into account
How are declining populations discovered?
- spatial variation in factors driving decline
- look for areas where factors driving decline are intense
e. g. habitat loss, over-exploitation, introduced species
How are declining populations discovered?
- biological traits
- idea that ecological and life history traits predispose species to population declines in response to human activities
e.g. body size
- hunting
- bigger animals mean
more food
- reproduction
- bigger animals have a
slower growth rate
What are the weaknesses of using biological traits to identify declining populations?
- Collen et al., 2011
- species traits weaker predictors than environmental traits
- Fritz et al., 2009
- geographic transferability is limited
- body size only a good predictor in the tropics
What is meant by the cause of a decline?
- demographic causes
e. g. reduced surival/breeding success/recruitment - environmental causes
e. g. poisoning from DDT/pesticides
How to diagnose cause of a decline?
- simulation model
Population Viability Analysis (PVA)
- requires knowledge of relationship between demographic traits & all external factors
- for most species, knowledge barrier too great to implement with sufficient speed
- need plenty of data
How to diagnose cause of a decline?
- comparative approach
- list plausible factors for decline
- identify populations that differ in these environmental conditions through time/space
- allows environmental factors causing decline to be identified
How to diagnose cause of a decline?
- comparative approach: timing
- compare timing & decline of environmental change
e. g. dramatic corncrake decline when machine cutting of hay (vs hand cutting) reaches 60%
What are problems with comparing timing?
several environmental factors often change simultaneously
- e.g. agricultural intensification
- more machinery/chemicals/hedge
removal/higher stocking densities
monitoring is too infrequent to identify precise timing of change in environment or population decline, e.g. many plants - spatial scale of population & environmental monitoring differ e.g. fish stocks & marine wildlife - time lags can distort relationships
How to diagnose cause of a decline?
- comparative approach: different environments
- use when not possible to compare populations pre and post decline
- can compare declined populations with undeclined populations at other sites
BUT
correlation does not always = causation
- positive correlation between rat poison & rat population doesn’t mean poison isn’t good for rats