Wildlife Ecology Midterm 1

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Kinazulu808
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Wildlife Ecology Midterm 1
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2010-07-18 22:13:36
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FW Wildlife Ecology
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Midterm 1
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  1. Biodiversity
    The sum of all lifeforms present in any given location (E.O. Wilson)
  2. Levels of Analysis
    Genes, populations, species, communities, ecosystems, landscapes
  3. Bacteria
    • Produces asexually instead of sexually
    • Liven in environments where carbon is not the basis of life (replaced by sulfar in deep thermal vents)
    • Do not need air
  4. How many species are there?
    • Estimate 5 to 30 million
    • 2 famous estimates
    • - Dr. Terry Erwin: entomologist (1982, Coleopterist's Bulletin)
    • - Dr. Robert May: theoretical ecologist (1992, Scientific American)
  5. Erwin's Estimates
    • S. American rainforest (Luhea seemanni, tree sp's)
    • Method: fogging trees catching dead bugs
    • Found 1100 bettles sp's, 160 specialized to canopy Luhea
    • 40% of all insects are bettles
    • Estimated 400 sp's specialized to L. Seemanii (160 of 40% of 400)
    • 2/3 of insects live in canopy, 600 total specialized in 1 tree (400 is 2/3 of 600)
    • 50,000 tree sp's in tropical forests, 30 mill. insect sp's in tropics(50,000 trees x 600 insects)
    • Insects 75% all known sp's (except 40 mill. sp's of life)
  6. What's needed to verify Erwin's Estimates?
    • Measure tree specificity of insect sp's
    • better sampling of canopy & terrestrial insects
    • Measure tropical tree diversity thoroughly
    • Lose about 300 tropical tree sp's/yr
    • Erwin: 300 x 600 = 180,000 arthropods lost/yr; 500/day
  7. Bob May Mathematics
    • Estimate diversity by looking at distributions of sizes of organisms (don't need to know identity of sp's)
    • Ecological principles limit the diversity of organisms as they get bigger (ex generation time)
    • Plot sp's # on log. scale on y-axis against log of orgnism size
  8. Genetic studies of Legionella penumophila
    • Organims sharing 50% of DNA considered same sp's
    • Equivalent to difference btwn fishes & mammals
    • Humans & chimps share 99% of DNA
  9. Any hope for cataloging biodiversity?
    • Taxonomists (7 % decline in U.S. & U.K. btwn 1980 & 1990)
    • Ageing pop. of systematics (63% over 46 yrs. old; only 8% younger than 35)
    • Mismatch btwn location of diversity & location of taxonomists
    • 80% scientists in N.AM./Europe, no latin Am. & tropical Africa/Asia
  10. Sp's distributed on earth?
    Depends on spatial scale of analsis & taxonomic group, but some major patterns apparent
  11. Spatial levels of analysis
    • Point Richness (single pt. in space)
    • Alpha Diversity (single habitat type/community)
    • Beta Diversity (multiple habitats/communities)
    • Gamma Diversity (entire regions/collections of ecosystems)
  12. Point Richness
    • Number of sp's at a single pt in space
    • Ex. Bird pt count
    • Problem: unknown area of habitat
  13. Alpha Diversity
    • Number of sp's in an individual community/ small "homogeneous" area
    • Some incorporate measures of abundance
    • Problem: detected w/in a single habitat
  14. Evenness
    • When all sp's have relatively same abundance: very even
    • All have extremely dissimilar abundances: very uneven
  15. Alpha Diversity
    • Low alpha diversity: few sp's, highly uneven
    • High alpha diversity: many sp's, even
  16. Distribution of biodiversity at the 'alpha diversity level'
    • Key correlations w/ increasing sp's richness
    • structural complexity of habitat
    • primary productivity
    • altitude
    • latitude
    • area
  17. Structural complexity of habitat
    • Positive correlation of sp's richness w/increasing complexity of habitat (in a certain region)
    • Ex. Bird Sp's (Grassland << shrubby fields << forests)
  18. Foilage Height Diversity Profiles
    • MacArthur
    • Habitats w/ greater complexity support more bird sp's
  19. Primary Productivity
    • Assimilation of energy & production of organic matter by photosynthesis
    • Greater primary porduction means more energy is available to support mroe sp's . . . up to a pt.
  20. Hump-shaped diversity curve
    Richness versus productivity
    • Produtivity - diversity paradox
  21. Paradox of Enrichment
    • Fertilizing sites w/ high sp's richness causes a decrease in richness
    • Salt Marshes, Hot Springs, Seasgrass beds highly productive; have few sp's.
  22. Altitudinal Diveristy Pattern
    • Fewer sp's w/ increasing elevation
  23. Latitudinal Diversity Gradients
    • Richness decreases w/ increasing latitude
    • Tropics have more species than temperate areas
    • Ex:
    • Ants 10 @ 60 degrees N; 2000 @ equator
    • Birds: handful at poles; 2500 @ equator
    • Exceptions: Marine
    • Marine Algae (peak 20-40 N)
    • Salamanders & Ichneumonid Wasps (Appalachian Mts)
    • Conifers (Boreal Zone)
    • Penguins (Antarctica)
    • Waterfowl (N. Temperate Zones)
  24. Islands
    • Fewer sp's than comparable area on mainland
    • General island patterns
    • - Richness Increases w/ (size, topographic (habitat) complexity)
    • - Decreases w/ isolation
  25. Beta Diversity
    • Degree of change in sp's composition across habitats
    • Cumulative number of sp's detected as move from one habitat to the next
  26. Species Accumulation Curves
    • Effort Curve
    • Plot number of sp's found versus measure of effect
  27. Beta Diversity Influenced By
    • Habitat specificity (degree of specialization)
    • Thought to be higher specialization in tropics
    • - geographic range sizes
    • - smaller in tropics (poorly known)
    • - altitudinal ranges smaller in tropics
  28. Gamma Diversity
    Overall richness across entire regions or landscapes (regional sp's pool)
  29. Diversity Measures
    • 2 components
    • Richness is # of sp's
    • Diversity is richness & pattern of abundance
  30. Measuring S (richness)
    • Sp's Accumulation Curve
    • Cumulative # of sp's found as a function of effort spent searching
    • - Time Spent Searching
    • - # of individuals identified
  31. Chao's Estimator
    S* = Sobs + (a2/2b)

    • S*: estimated # of sp's
    • Sobs: # actually found & identified
    • a: # of sp's where we saw only one individual (singleton sp's)
    • b: # of sp's where we saw 2 individuals (doubleton sp's)
  32. Chao's Variance
    • VarianceChao = b[{c4/4) + c3 + (c2/2)
    • C= a/b
  33. Confidence Interval
    • Approximate a confidence interval w/ 2 times standard deviation
    • Explains if our observed S fall w/ in 2 standard deviation of our estimated S*
    • Square root of variance is equal to the standard deviation
    • 1 S.D. above & below a mean = 64% all possible estimates
    • 2 S.D. = 96 %
    • Calculate by:
    • S.D. = square root variance
    • S* = S* +/- 2(S.D.)
  34. Simpson's Diversity Index
    • D = 1/SUMpi2
    • Calculate proportion of all individuals represented by each sp's
    • pi: fraction of individuals out of the whole sample of organisms that are of a certain sp's
    • Steps:
    • Square each proportion
    • Add them together
    • Diveide # into 1
  35. Shannon- Eaver Index
    • H' = -SUM [pi*ln(pi)]
    • Calculate fraction of all individuals represented by each sp's
    • Take natural log (loge) of each pi value
    • Multiply pi times ln(pi) for each sp's
    • Sum all those products
    • Take the negative to get H'
  36. Species area relationship
    • Space increases in site, # of sp's in space increase
    • Bases for wildlife ecology:
    • - biogeography theory: bigger islands have more sp's than smaller islands
    • - conservation strategies: big reserves will preserve more sp's than small reserves
    • - predictions of how habitat loss will affect species richness
  37. Sp's Area & Power Curve
    • S = cAz
    • logS = (log c) + z (log a)
    • S = # of sp's
    • C = constant measuring # of sp's per unit area
    • A = area of island
    • Z = Constant measuring slope of line relating to S and A
  38. Use relationship to protect sp's losses
    • Inventory plots of various sizes
    • construct sp's area graphs
    • predict effects of habitat loss
  39. Area Sensitive Sp's
    sp's occuring only in habitats/ islands/ reserves of a certain size or larger
  40. Incidence Functions
    • Best Studied in Vertebrates
    • shows the frequency of occurence of a sp's w/ respect to habitat patch area
  41. Incidence function calculations
    • survey many sites for a sp's
    • sites need to range in sizes
    • need method for ensuring detection of sp's of interest
    • generate graph of occupancy vs. size of area surveyed
    • look at shapes of incidence functions to determine area sensitivity
  42. Who's the most vulnerable to fragmentation?
    • Wide ranging sp's (mt. lion: food occur sparsley/ hard to catch)
    • Naturally rare sp's (ivory-billed woodpecker: old growth swamps & trees)
  43. Sp's of limited mobility
    • immigration btwn patches might be eliminated, therefore reducing persistence
    • dung beetle (beetles), amphibians (salamanders), some tropical birds
  44. Sp's with low fecundity
    inability to adjust to different levels of predation in fragments; can't reproduce frequency enough to offset higher predation
  45. Ground nesters
    • if populations of terrestrial predators increase in fragments, ground nesters decline
    • ex. racoons
  46. Sp's vulnerable to human exploitation / persecution
    • fargmentation allows easier human access, increase negative encounters (road kill)
    • ex. parrots (tree cavities, low pop. densities)
    • - breed in small fragments = high chance person locate nests
  47. Sp's with short life cycles
    failure to reproduce in successive yrs. might doom popoulation; longer lifespan increases chances of success
  48. Sp's dependent on patchy resoruces
    patchy resources may not be plentiful in smaller fragments; may occur irregularly in time
  49. Interior Sp's
    some sp's require resource found only deep w/in patches (microclimate conditions, food, etc)
  50. Why does fragmentation affect soem sp's
    • Reduction in total areas of habitat
    • Edge effects
    • Ecological Traps
  51. Edge Effects
    • Edges are transition zones btwn habitat types (ecotones: boundaries btwn natural communities)
    • some predators sp's proliferate in disturbed habitats
    • Microclimatic changes alter habitat (more sunlight, drier, more wind exposure)
    • Structural changes in habitat (increased veg. density, more weedy sp's, more treefalls)
    • Parasites increase in abundance
  52. Brood Parasitism
    • Parasitize the parental care of hosts
    • Female find the nests of songbirds & lay their eggs & leave them
    • Go find another nest to do same (up to 40 or more)
    • Find nest w/ eggs same size or smaller
    • Ex: Cowbirds
  53. Reduce RS of hosts
    • Often remove host egg(s) when laying cowbird egg
    • Cowbirds eggs hatch first
    • Young get most of food
    • Sometimes eject host eggs or young
    • Some hosts do not recognize that cowbird is not thier own, so don't breed again that yr.
  54. History of cowbirds
    • Native to great plains
    • Followed bison (nomadic, lay egg & leave)
    • Not a forest sp's, so parasitized grassland sp's
    • Grassland sp's adapted to tolerate parasitism and/or recognize cowbird eggs & eject them
    • Forest clearing allowed range expansion to east & west
    • Continental build up in #'s
    • Access to native host sp's not able to compensate for brood parasitism
    • Now parasitize over 100 sp's of songbirds
    • Max commuting range 7-10 km (Large forest provide habitat for songbirds)
  55. Corea Area
    • Portion of a fragment that is not influenced by edge effects
    • Dependent on shape
  56. Ecological Traps
    • Situations where habitat structure attracts individuals, but biotic alterations reduce reproductive success
  57. Habitat Loss
    • Area has been reduced & expect decline in sp's richness to occur becasue of reduction in habitat
    • - primary factor causing sp's to become rare & endangered
    • Happens for all habitats, but we'll focus on forests
    • Examples
    • - USA: 1620 - Pilgrims 1st, forest extensive (a lot)
    • - Costa Rica: Lost 70% of forests in 45 yrs
  58. Predictable sequence of forests loss
    • Cadiz Township in Wisconsin
    • -1831: area covered by forests (farmers colonized area & began to cut trees, forest became distributed as isolated patches)
    • -1902: few larger patches were left
    • - 1950: dominated by agriculture & only few small isoated patches
  59. Perforation
    • Forman's Categories
    • Initial stage of fragmentation
    • - clear cuts, developement of homestead, slash & burn
  60. Dissection
    • Forman's Categories
    • Creation of linear strip of deforested habitats
    • - Creation of roads /powerline corridors
  61. Fragmentation
    • Forman's Categories
    • Isolated patches of habitat by removing some forest from landscape
  62. Shrinkage
    • Forman's Categories
    • Loss of area from habitat patches
  63. Attrition
    • Forman's Categories
    • total loss of patches
  64. Faunal Relaxation
    Loss of sp's through time after isolation
  65. Super Saturation
    • Fragment during spike, has more sp's than expected given its area
  66. Biological Dynamics of Forest Fragments Project
    • Manaus, Brazil
    • - Cut trees to isolate several 1, 10, 100 ha fragments
    • Found faunal relaxation
  67. Extinction Debt
    • Expected # of sp's losses based on sp' area equation
  68. Sp's isolation relationships
  69. Why sp's disappear from fragments
    • Sp's area effects: habitat is lost, area declines
    • Sp's isolation effects: poor dispersers don't recolonize after extinctions
    • Sp's environment effects: changes in abiotic conditions after habitat quality
    • Sp's interaction effects: changes in food web organization

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