BIOLOGY 304
                   ECOSYSTEMS

 


Introduction:  The same information in new perspective:  See p. 294?      The first part is just
Critters in Community Context
The other parts focus more on the system than on its components.  The other parts are
     Species Richness and Diversity   and     
     Functions:  Energy & Matter Processing
 

Critters in Community Context.  See fig. 9.1 and p. 331 #1 -->   Critter File 4  (CF 4)
Since the next week or so is based on the same information, you will be expected to contribute to class discussions based on textbook concepts applied to relevant questions from the next Critter File.  (And it will be just about finished several days before its due date.)  Then we will move to more and more emphasis on the ecosystem as a whole and less on its critter components.    
 

  • [9a] Critter Compromises. (295-308)   (Monday, 17 Mar)
    Which selection factors are the strongest forces in your critter's evolution?-->   CF 4 
    To answer you need to consider:
    • Where does it belong in a food chain?  Which other species does it interact with?  Do the other species regulate your population's density or dispersal or dispersion?  Does your critter affect other populations' densities or dispersal or dispersion?
      In nature, is your critter's population density relatively stable, or does it fluctuate?  If it's stable, like the buttercup here or the swifts in the textbook, (or even if it fluctuates) do the patches within the population have fluctuations in mortality or immigration or fecundity or growth?
      Is your critter abundant or rare?  How do you know?

      Is its abundance determined by density-dependent regulation or is its abundance determined by density-independent factors?  How do you know?
         
      One approach = key factor analysis (See p. 302ff)
      The first step is to document critter's life history, like in fig. 5.5 (p. 164), only better.

      Then for each stage in the life history you document the mortality factors and their "killing power" or k-values, like in Table 9.1 on p. 302.
      But the key to key-factor analysis is to have k-values for several years or several locations so that you can pin-point the fluctuations in killing power and therefore abundance. 

      Once you pin-point which key-factors fluctuate, then you can figure out whether the killing-power fluctuations are density-dependent.
      If the killing-power fluctuations are density-dependent, you can conclude that the critter's abundance is regulated.  If the fluctuating key-factors are not density-dependent, you know that its abundance is determined by stochastic factors or something not density-dependent, even though it has some density-dependent key factors..
      For your critter, you'd be extremely lucky to find enough data to do real key-factor analysis; so you don't have to worry about how they calculated regression coefficients and probabilities in the textbook examples.  However, you should use your imagination to plan a key-factor analysis and predict where you'll find the fluctuations.  You should make a chart like table 9.1.  Don't worry; you don't have to do the experiment, just design it.
    • Other approaches.  See American Naturalist for the latest ideas:
    • Questions #1, 2, 4 (p. 331)
    •  
  • [9b] Critter Metapopulations in patches.  (308-319) (Wednesday)
    The metapopulation concept marks a transition from analyzing each species individually to a community perspective of  patches potentially occupied by your species or other species.
    • What is your critter's dispersion (random, clumped, or what?) and dispersal (how does it colonize or migrate?)?   Can it rescue patches in peril to prevent extirpation?  Does it have a functional metapopulation?--> CF 4
      • Review metapopulations pp. 287 ff
      • and review Lab 2 background. 
        • If wild onions have a random dispersion, then a Westfield Road sample will match a Poisson distribution.  or
          If wild onions have a clumped dispersion, then a sample of quadrats from a floodplain lawn will be significantly different from a random distribution and the sample variance will be higher than the sample mean.
        • "Therefore I reject the null hypothesis in favor of the alternative hypothesis that the distribution was aggregated."
        • p=_____.    Ho:________________   (preferably on Figure 1)  more about p
        • hypothesis is only the "If" part (null hypothesis could be the "then" sometimes)
          • the expected numbers were for a random dispersion = Poisson distribution,
          • expected frequencies were calculated using Excel's Poisson function
          • mean, variance, chi-square values and p were calculated....   (report them on figure legend) 
          • report quadrat size (preferably in cm); sample size is on figure; omit other details assuming that all readers understand SOP
          • frequency distribution graph y axis labels
        • Biological importance?
      • and review Island Biogeography Theory (also summarized on box 9.3, p. 310)
    • Are your critter's patches dominance-controlled or founder-controlled, and why does it matter?  And at RibbonWalk and elsewhere, your critter would be found in the habitats which are at which stage of succession?  Is your critter a "fugitive species" ?              ---> CF 4
    •  
    • In founder-controlled patches (or gaps withinin the community), stochasticity is the biggest factor in determining which species are abundant. 

       "The detailed sequence of occupancy is therefore unpredictable.  Species richness remains high and relatively constant."
      In dominance-controlled patches (or gaps withinin the community), interspecific competition  is the biggest factor in determining which species are dominant (abundant). 

      "...the occupancy of gaps is reasonably predictable...."
      Is species richness predictablbe?
      review of succession
      fig. from Freeman, Biological Science

      analogous events
      occur in other biomes

       
      "Early species are good colonizers and fast growers, whereas later species can tolerate lower resource levels and grow to maturity in the presence of early species, eventually outcompeting them"

      American ecologists now usually avoid the term "climax" (in its ecological sense) because we view succession as a trajectory in which changes in species abundance merely slows as gap availability slows in late succession.  "Climax" was formerly defined as a stage in which species composition remained unchanged.
      from email:  I posted a query on ECOLOG in 1999, requesting information on spatial studies of forest succession. I received 32 responses from colleagues around ECOLOG - Many thanks.  Based on your responses, and further review of literature, we developed a spatially stochastic model for boreal forest succession. This model is designed to generate spatially-explicit null hypotheses for modeling and field studies. This model was published in ....Ajith H. Perera, Research Scientist & Program Leader, Forest Landscape Ecology Program, Ontario Forest Research Institute ajith.perera@mnr.gov.on.ca
    •  
    •  
    • Now is a good time to re-examine your critter in terms of the  r and K spectrum, because these concepts help explain dominance- and founder-control and your critter's role in natural succession.
    • Questions #5, 6, 7 (p. 331) and also critique the use of "control" in "dominance- and founder-controlled" in reconsidering question #4 (regulation/determination).
    •  
  • [9c] Critters in Food Chains (317-331)  (Friday)
    • Is your critter a  real player (maybe even a keystone) in its food web, or is it more like just on the receiving end of the various direct and indirect effects of the players?  Have you already identified the real players above?  If not, who are they?--> CF 4
    •  
      Be able to explain the figure on the left and to compare this explanation to the figure on the right (from chapter 1 and the midterm exam).

      		In looking at fig. 9.13 on the left, in which row and column would you place your critter?  Do the relative importances of predation and competition match your earlier analyses of which were the stronger selection pressures in your critter's evolution? 

      Is your critter's food web at RibbonWalk (or elsewhere if necessary) controlled bottom-up or top-down?  Does your critter act like the world is green or prickly-and-bad-tasting?  Explain.  Does this perspective on control of your critter's food web have any relevance to your critter's key factor analysis or other analysis of its selection pressures or population control?  -->  CF 4
       

      Community stability:  What does the textbook say about the relationships among stability and complexity and species richness?  How could you argue with the authors?  Does your critter have any "real player" impact on community diversity or stability?  Or is your critter's abundance or extinction imperiled by changes in biodiversity?  Explain.  --> CF 4
      see fig 9.17 in text
       

      fig 9.16(right)   inconsistent relationships between connectance & richness

      Figure 9.18 (left):  Can you find errors in its legend (p. 327)?
       

      Community stability:  What are other researchers saying these days?
       http://www.sciencemag.org/
      cgi/content/full/296/5570/1035       

      could this explain the inconsistencies on fig 9.16?

      do your critter's food web and biomass pyramids look like these?

      http://www.sciencemag.org
      /cgi/content/full/296/5570/1120

      		1. Stability is improved by connectance which includes more weak links and shorter and fatter pyramids:   "...long loops that contain many weak links, a feature that enhances stability by reducing the average interaction strength of each loop. Longer loops are especially important in this respect because they are potentially destabilizing.  The groundwork for these ideas was laid by May's analysis of model systems (3). His analysis revealed that complex webs tended to be less stable than simple webs, a finding apparently at odds with the observation that real food webs are highly complex yet stable. One way in which this paradox can be resolved is if the average strength of interactions between species is low, and this is exactly what Neutel et al. have found. McCann and colleagues (4) came to similar conclusions, that is, a high proportion of weak interactions in webs contributes to their stability. However, Neutel and co-workers have gone a stage further by demonstrating that the organization of strong and weak linkages in food webs seems to be reflected in the shape of the biomass pyramid itself. This occurs because energy conversion efficiencies and body size depend on trophic levels. Thus, large long-lived animals with higher energy efficiencies, such as carnivores, are found in trophic levels near the top of the pyramid. It follows that the slope of the side of the pyramid may be a good indicator of web stability: Webs that give tall, thin pyramids are less likely to be stable than those with shorter, more squat pyramids" 

      movie http://www.sciencemag.org/
       cgi/content/full/299/5611/1388/DC1

      		2. Prey switching (adaptive foraging) increases stability:  Foraging Adaptation and the Relationship Between Food-Web Complexity and Stability (Michio Kondoh):  "Ecological theory suggests that complex food webs should not persist because of their inherent instability. "Real" ecosystems often support a large number of interacting species. A mathematical model shows that fluctuating short-term selection on trophic links, arising from a consumer's adaptive food choice, is a key to the long-term stability of complex communities. Without adaptive foragers, food-web complexity destabilizes community composition; whereas in their presence, complexity may enhance community persistence through facilitation of dynamical food-web reconstruction that buffers environmental fluctuations. The model predicts a linkage pattern consistent with field observations."
      http://www.sciencemag.org/cgi/content/full/299/5611/1388 
      ".Disturbance tends to cause a temporal decrease in realized connectance. Time required for recovery of realized connectance decreases with increasing adaptation rate."
      "Disturbance initially causes a strong fluctuation in food-web linkage,...(Movie S1),where many potential resources may not be used at all while a few "profitable " resources are used.  As a result,realized connectance tends to be low in this phase. Eventually,food-web architecture stabilizes,and the realized connectance increases to recover."
    •  
    •  
    • Questions #8. 9. 10 (p. 331) and this:  fish caught these days are lower on the food chain.  Why does that matter to you or your critter? http://americanscientist.org/articles/00articles/Pauly.html 
    •  
    •  


Species Richness and Diversity

  • [10a] Monday.  Textbook pages 332-347.  Skip the parts on rank-abundance diagrams & fig. 10.2
    • Compare richess/diversity; index/indices, niche breadth/niche overlap
    • "...richness of different communities should be compared only if they are based on the same sample sizes (in terms of ____, _____, or, best of all __________)." p. 333 end of 2nd paragraph
    • Draw (at least in your head) a real-life example of figure 10.3, with a specific measurable resource and realistic, typical critters. Which example best matches your critter and its competitors?
    • (in lab the Shannon-Weaver math will be demonstrated)
    • To do the domino questions below, consider these points of logic (plus whatever is in the book):
      • richness depends on the probability that each species there can persist
        despite competition, predation, lethal parasitism, stochastic effects on its population growth, etc.
      • richness also depends on how likely it is that different species have the dispersal ability and numbers of dispersal units to get there
      • and richness also depends on how long the habitat and its conditions have existed; if it's relatively young and rare, maybe only a few species have had a chance to evolve adaptations suitable for it.
    • List the "dominoes" or links in a causal (not casual) chain-of-events explanation for each of these generalizations (fill in the hypothetical blanks between arrows) (remember that correlation does not = causation): 
      • Increased productivity -> ->  ->    -> increased richness
      • Increased evapotranspiration fig. 10.4 ->   ->  ->-> increased plant species richness
      • Increased evapotranspiration fig. 10.5  ->->  ->-> __creased animal species richness
      • Increased nutrients -- fig. 10.6-b, c, d )-> increased productivity ->->  ->-> decreased richness (paradox of enrichment)
      • Increased predation or parasitism  fig. 10.7->  ->   ->  -> increased richness
      • Increased predation or parasitism ->  ->   ->  -> decreased richness
      • Increased spatial heterogeneity   fig. 10.8a->->->  ->   ->  ->      _creased plant richness
      • Increased spatial heterogeneity  fig. 10.8c->->->  ->   ->  ->    __creased animal richness
      • Increased environmental harshness  fig. 10.9 (pH)->->  ->   ->  ->
      • predictable climate change  fig. 10.10 ->->->
      • Increased unpredictable climate variations -->-->->  ->    ->  ->-->
      • Increased intermediate disturbance  fig. 10.12-->->  ->   ->   ->-->-->
    • Answer these questions on p. 367: #1, 2, 3, 4, 6

  • [10 b] Wednesday  Textbook pages 347-366
    • Continue the domino game on these:
    • Be sure you completely understand MacArthur & Wilson's Biogeography Theory (Box 10.2, pp. 350 ff.,  fig. 10.14
    • Answer these questions on p. 367: #7, 8, 9, 10
    • Make up your own hypothesis of species richness:

 

FUNCTIONS, Cycles, Chains, Circuits, & Webs

11a:  Friday.  Textbook pages 368-385. 
  • The most important concept in the chapter is ______
  • Everything in the chapter is about either describing or explaining these truly life-threatening patterns:
  • So be sure that you can connect all the details (especially and fig. 11.1 and fig. 11.3 and fig. 11.4 and 11.5  and fig. 11.7 and fig. 11.8) to these two deals, as in these questions at the end of the chapter:  #1,2,3,4,5,6,7

 
11b: the next Friday>  Textbook pages 386-395
  • The most important objective here is to be able to explain, in detail, all the diagrams,
  • especially fig. 11.16.
  • Can you answer these?  #8,9, & 10
  

If you're not sure you can achieve this objective,

 
  • Critters in Biomes (Review Chapter 4)
    Which biomes or major habitat types contain your critter?  How much of your critter's dispersion and abundance is controlled by the abiotic (physiochemical) aspects of its niche?  How important were specific abiotic factors as selective forces?   (What adaptations does it have for these physiochemical extremes?)
  • SUMMARY. Here are some characteristics of communities and ecosystems:
    • diversity, richness, evenness
    • relative abundance of dominant types (but not density or demography of the populations)
    • spatial and temporal structures (e.g., zonation, canopy layers, patches and gaps, maybe flowering and fruiting and leaf-shedding seasons but not phenology or life-history characteristics of the populations )
    • ranges of resources/conditions (= niche axes) 
    • average niche breadth and overlap (but not the niche itself)
    • heterogeneity of structures and resources and conditions
    • food web trophic levels, links, connectance, control
    • productivity, efficiencies (which can also apply to the populations)
    • mineral cycling rates and reservoir concentrations, leaks
    • stability

 

LINKS to MORE Ecosystems stuff

 

                                    


PROTOCOLS for SAMPLING & ANALYSIS (SOFTWARE and Professional Stuff)

  • There you will find for example a 'pdf' file: www.env.duke.edu/lel/env352/alt_maps.pdf this file discusses the uses of spectral analysis (and wavelet analysis) in ecology.

  • http://www.env.duke.edu/landscape/

  •  "We use spectral analysis all the time in remote sensing (its the core of what a remote sensor does). There is a wealth of literature on the subject -- you can check out our lab's website at www.cstars.ucdavis.edu , we use an imaging spectrometer (AVIRIS) to produce images where each pixel has a continuous spectrum in which we can analyze absorption features, perform wavelet analyses, and just about anything else you can think of doing with spectrum, and then scale in the information across a landscape... I'd argue this is the most advanced use of spectral analysis in ecology... We can do neat things like calculate LAI, biomass, leaf water content, canopy structure, species assemblages, etc, etc... from Jonathan Greenberg <greenberg@UCDAVIS.EDU

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