Niche & Life History
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Definition & History of the Niche Concept
Variability and Tradeoffs in Nature
Life History
Functional Types
Readings:
-­‐Chapter 9 (today)
-­‐Lavorel et al. 1997 Plant Functional Classifications. TREE 12:474-­‐478 (Friday)
Evolution of the “Niche” concept
• A hole in the wall – the place where a species lives.
• Grinnell (1917, 1924) – a species’ physical environment (habitat)
• Charles Elton (1927) – a species’ biotic and abiotic environment
George Evelyn Hutchinson
Yale Scientific
Defined a the niche as an “n-­‐dimensional hypervolume”
Introduced the concepts of “fundamental niche” and “realized niche”
Hutchinson’s niche extends the concept of tolerance limits to multiple (n) dimensions
2-­‐dimensional niche space
temperature
Fig. 5.8
Molles & Cahill 2008
3-­‐dimensional niche space
This tolerance diagram represents a 1-­‐dimensional niche space
temperature
… where n is the number of biotic and abiotic environmental factors important to the survival and reproduction of the species.
Fundamental vs. Realized Niche
• Fundamental niche
– Maximum possible niche size in the absence of other species
• Realized niche
– Actual niche considering effects of other species
Fig. 9.2, Molles & Cahill 2008
http://www.chebucto.ns.ca/ccn/info/Science/SWCS/PEOPLE/PIC/hutchinson_tree.jpg
• Remember that “niche” is an abstract concept that is impossible to fully measure (although people have tried!).
• For practical reasons, measurements of “niche space” are typically restricted to one or a few dimensions.
Habitat niche of Spartina anglica
(salt marsh grass)
Fig. 9.8, Molles & Cahill 2008
“Feeding niches” of Galapagos finches
Fig. 9.3, Molles & Cahill 2008
Niches can be dynamic -­‐ Beak size evolves and niche space changes as environments change
Fig. 9.6, Molles & Cahill 2008
Variation & Tradeoffs
What drives variation in seed shape and size?
Fig. 9.13, Molles & Cahill 2008
Seed mass vs. seed number
Fig. 9.14, Molles & Cahill 2008
Factors correlated with seed size & shape
Dispersal mechanism
Wind-­‐dispersed
Adhesive?
Vertebrate?
Fig. 9.15, Molles & Cahill 2008
Factors correlated with seed size
Plant growth form
http://en.wikipedia.org/wiki/Tree
http://en.wikipedia.org/wiki/Forb
http://en.wikipedia.org/wiki/Graminoid
Fig. 9.15, Molles & Cahill 2008
http://en.wikipedia.org/wiki/Vine
Bigger seeds make bigger plants!
Fig. 9.18, Molles & Cahill 2008
But are there disadvantages to being big?
Greater reproductive effort is often linked to greater mortality
Reproductive effort = allocation of energy, time, and other resources to the production and care of offspring. Note that many species exhibit flexibility in this trait.
Figs. 9.20, 9.21, & 9.25, Molles & Cahill 2008
Tradeoffs exist between reproduction, survival, growth, etc. Fig. 5.34, Molles & Cahill 2008
Organisms cannot simultaneously maximize all functions; they must “optimize” their efforts among different functions depending upon biotic and abiotic environmental conditions. The particular balance that a species exhibits defines its “life history”
Life History
• How an organism divides its effort between reproductive effort, growth, age at reproductive maturity, longevity, etc. • Describes the “life pattern” of a species
• Provides a convenient way to classify organisms according to their ecological function.
Life History Classification
• Ecologists have classified organisms according to a few characteristics defining their “life history”
– r and K Selection (MacArthur & Wilson 1967)
– Plant Life History “Strategies” (Grime 1979)
– Opportunistic, Equilibrium, and Periodic Life Histories in Fish & Vertebrates (Winemiller & Rose 1992)
– Reproductive Effort, Offspring Size, and Benefit-­‐Cost Ratio (Charnov 2002)
r vs. K selection
Fig. 9.29 – Molles & Cahill 2008
Grime’s Plant Life History Strategies
(adds an extra dimension to the r-­‐K system)
(K-­‐selected) r-­‐selected
Fig. 9.30, Molles & Cahill 2008
Opportunistic, Equilibrium, & Periodic Life Histories (tradeoffs between fecundity, survivorship, and age at reproductive maturity)
(r-­‐selection)
K-­‐selection
Fig. 9.31, Molles & Cahill 2008
Opportunistic, Equilibrium, & Periodic Life Histories (tradeoffs between fecundity, survivorship, and age at reproductive maturity)
Fig. 9.32, Molles & Cahill 2008
Reproductive Effort, Offspring Size, and Benefit-­‐Cost Ratios
Charnov’s Life History Cube
(uses dimensionless axes)
Figs. 9.33 & 9.34, Molles & Cahill 2008
“Functional types”
Lavorel et al. 1997 Plant Functional Classifications. TREE 12:474-­‐478 Plant functional types
• Driven by the need to understand vegetation responses to environmental factors (in the context of climate change or disturbance).
• Species are too fine a grouping to be tractable on a global scale; we need a simpler classification system that captures organisms’ functional properties from an ecosystems perspective.
Dynamic Global Vegetation Models
Current functional type classifications draw on several concepts:
Morphology & “Life form”
Life history traits
Plant size/seed mass
Growth rate
Grime’s CSR strategies
Physiological traits:
C3/C4/CAM physiology
Nitrogen-­‐fixing/non-­‐fixing
Responses to disturbance fire
grazing
regeneration ability
Note that there is no universal agreement on what constitutes a “functional type” –
consequently, the concept is applied in an “ad hoc” manner depending upon the context
Example – response to disturbance
Fire in Southern California as seen by NASA’s AVIRIS sensor Bromus is an invasive species that benefits from disturbance.
Bromus sp.
Wildfire
Nitrogen deposition
Elevated CO2
In Grime’s CSR scheme, Bromus would be called a “ruderal” (weedy) species.
http://www.ext.colostate.edu/PUBS/NATRES/06310.html
Red brome invasion in the Mojave Desert is enhanced by disturbance
Nevada Desert Face Facility
http://www.intranet.csupomona.edu/~jcclark/flora/plants/poaceae/bromus_madritensis.html
Using remote sensing to classify functional types (optical types) based on biochemical content detectable from optical signatures
Asner and Martin 2009
Normalized biochemical content of tropical Hawaiian species
Asner and Martin 2009
Spectronomics – classifying vegetation according to spectral space
Asner and Martin 2009
Remote sensing of biological invasions using spectral signatures
Asner & Vitousek 2005
http://www.botany.hawaii.edu/faculty/gardner/biocontrol/myrica%20faya/myrica.htm
Proposed concept of functional types based on remote sensing (“optical types”)
Gamon & Ustin 2010
"What's the use of their having names," the Gnat said, "if they won't
answer to them?"
"No use to them," said Alice, "but it's useful to the people that name them, I suppose. If not, whey do they have names at all?"
-­‐ Lewis Carroll, Through the Looking Glass.