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Niches What is a niche?. Niche Theory You can think of it as its ‘address’

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Presentation on theme: "Niches What is a niche?. Niche Theory You can think of it as its ‘address’"— Presentation transcript:

1 Niches What is a niche?

2 Niche Theory You can think of it as its ‘address’

3 What is a niche? A multidimensional expression of where or how a species lives

4 Niche Theory Generalist vs. Specialist

5 Niche Theory Why the hump in the curve? Consequently, they taper off at each end of the resource spectrum becoming less competitive at either end Because there is an optimal ‘size’ or space on the resource continuum

6 Realized vs. Fundamental Why might a sp. not completely occupy its fundamental niche?

7 Fundamental vs. Realized

8 Niche Breadth What are some of the factors that impact niche breadth? Competition Predation Resource predictability Resource abundance Intraspecific competition (ind. vs. pop)

9 Niche Theory Despite its conceptual simplicity, observing niche competition is not so easy A basic premise, in the presence of a strong competitor, niche breadth should change (short term through behavioral modifications and long term through evolutionary adaptations)

10 Fundamental vs. Realized

11 Niche Theory Huey et al. (1974) demonstrated that 2 sp. of skinks appear to have large dietary overlap of termites when population adjacent, but shift away from one another when sympatric Furthermore, at the end of sympatric distribution, the smaller sp. quickly displayed a significant increase in body, head, and jaw size

12 Niche Theory This dramatic change is frequently associated with character displacement What is the problem with documenting character displacement?

13 Niche Theory We may observe current patterns in an attempt to determine past events One example is that adaptive radiations and subsequent ‘regular spacing’ on resource axes

14 Niche Theory However, different size bills and bodies can also simply reflect diet specialization (i.e. just getting better) There are several clusters of similar species that have developed differences in foraging areas and that is an indirect indication that competition may have been at work (previously)

15 Niche Theory Tyrannid flycatchers; perhaps an example of past competition

16 Niche Theory Foraging relationship among several antbirds (Formicariidae) showing ecological separation

17 Niche Theory Projected niche relationships in 2 resource space

18 Niche Theory Ecological segregation should work to minimize competition and niche overlap

19 What is niche overlap? Species can be generalists and have relatively high niche overlap and compete strongly with other species

20 What is niche overlap? Species can either separate and minimize competition (lower the niche overlap) by becoming a resource specialist (a)

21 Niche Breadth (width or size) Some plants and animals are more specialized than others, and measures of niche breadth attempt to quantify this It is typically measured by observing the distribution of individual organisms within a set of resource states Information is collected and presented in a resource matrix

22 Example of a Resource Matrix The percentage utilization of 14 microhabitats by 11 species of SW desert lizards

23 What are common resource states? Resource states may be defined in a variety of ways: 1)Food Resources: taxonomic identity of food taken may be used as a resource state, or the size category of food item (without regard to taxonomy) could be defined as the resource state

24 What are common resource states? 2) Habitat Resources: habitats for animals may be defined botanically or from physical-chemical data in a series of resource states 3)Natural Sampling Units: sampling units like lakes or leaves or individual fruits may be defined as resource states 4)Artificial Sampling Units: a set of random quadrats may be considered different resource states

25 Niche Overlap Shared niche space of the Hutchinsonian multidimensional niche Thought to represent a measure of competition intensity

26 Levin’s Measure Niche breadth be estimated by measuring the uniformity of distribution of individuals among the resource states B = Y 2 / ∑ N 2 j where B = Levins measure of niche breadth N j = Number of individuals found in or using resource state j Y = ∑ N j = Total no. of individuals sampled

27 Shannon-Wiener Measure Others have suggested using the S-W formula from information theory to measure niche breadth H’ = -∑ p j log p j This measure tends to weight rare resources (compared to Levin’s, which weights common resources)

28 Niche and Communities Community change in the limiting similarity model comes about through repeated colonization and extinction of species with different utilization curves If adjacent species are ‘too close’ together, one of the pair will go extinct, depending on the overlap and the carrying capacity of the environment (Gause’s competitive exclusion principle)

29 Niche and Communities After repeated C & E events, an equilibrium is reached with a maximum number of coexisting species separated by a critical minimum spacing (Gotelli Fig. 4.1)

30 Niche Overlap One way to understand community organization is to measure the overlap in resource use among the different species in a community The most common resources measured in order to calculate overlap are food and space Several measures have been proposed, with various strengths and weaknesses

31 Niche Overlap Historically, analyses of niche overlap were based on the theory of similarity (MacArthur and Levins 1967) However, this early measure was asymmetrical and has since been replaced by a more symmetrical measure Overlaps calculated this way have been equated with the competition coefficients of the Lotka- Volterra equations and are thus proportional to the intensity of competition

32 MacArthur and Levins Overlap ∑ p 2i p 1i O 21 = ∑ (p 1i ) 2 Asymmetrical Competition (impact of sp1 on sp2 is not the same as that of sp2 on sp1)

33 Pianka’s Overlap ∑ p 2i p 1i O 12 = O 21 = √ ∑ (p 2i ) 2 ∑ (p 1i ) 2

34 Czekanowski’s Index O 12 = O 21 = 1 – 0.5 ∑ |p 1i – p 2i |

35 Percentage Overlap This is a very attractive measure as it is relatively easy to calculate and interpret P jk = [ ∑ (minimum p ij, p ik )] * 100 where P jk = percent overlap between j and k p ij & p ik = proportions resource i is of the total resources used by species j and k and n = total number of resource states

36 Morisita’s Measure C = 2 ∑ p ij * p ik / ∑ n p ij [(n ij -1)/(N j -1)] + ∑ n p ik [(n ik -1)/(N k -1)] This measure is free from bias over a range of possible values and is a relatively good measure of overlap

37 Null Model Decisions Weighted vs. Unweighted Indices If all resources states are not equally available, observed overlaps in utilization may not accurately reflect similarity in use In particular, if some resource states are extremely common and others are extremely rare, species may appear very similar in their resource utilization

38 “electivity” Ecologists have suggested modifying existing indices to account for the electivity, (the relative ability (or preference), of resource use Incorporating resource availability may have a major effect on measures of overlap (e.g. think about large use; could be abundant resource or high preference)

39 Pairwise Niche Overlap

40 EcoSim

41 Weighted vs. Unweighted If resource states are not equally abundant, observed utilizations will tend to overestimate the amount of ecological overlap (i.e. everyone is using abundant resources) However, it can also correct for uneven resources For example, only 2 of 10 mean utilization overlaps for Pianka’s (1967) NA lizard communities differed from null models whereas all 10 mean electivities differed significantly This approach has problems as well, see book

42 To generate a null model to test for deviations from expected (for overlaps), we need to construct a null model We could 1) randomize the dietary or activity data OR 2) randomize species occurrences

43 Niche Overlap & Species Occurrences If competition limits niche overlap, then the particular combination of species that coexist on the island should have lower overlap than a randomly assembled set of species from the same source pool (Gotellli and Graves)

44 Randomization of species occurrences How to generate a null model for niche overlap of 18 species of lizards on 37 islands in the Sea of Cortez? Using biologically realistic criteria, Case (1983) identified a source pool of 18 mainland species that could potentially colonize each island For each island with i species, Case enumerated all the unique ( 1 i 8 ) combinations of exactly i species as null communities

45 Example Species coexisting on islands had lower niche overlap (30 of 37 times) than would be expected in the absence of competition (or a nonrandom pattern of resource availability)

46 however, this analysis assumed that species colonized islands equiprobably When %occupied was used instead, only 23 of 27 fell below the median This suggests that dispersal ability may have contributed to the pattern of reduced overlap

47 Wait… What is low overlap was a result of nonrandom patterns of resource availability on islands? If the same nonoverlapping sets of resources were present on several islands, the same combinations of low- overlap species would be found

48 For most island size classes, an improbably small number of species combinations was represented SO? This suggests the same low-overlap configurations tended to recur. Consequently, the pattern initially observed probably resulted from a nonrandom distribution of resources and NOT competition

49 Null Model Example Schoener (1988) also examined niche overlap of island lizard species sampled from a larger source pool, but examined microhabitat use Coexisting species usually differed in the structural habitats they occupied e.g. on two-species islands, each species occupied a different category; coexistence in the same habitat was found once on 3-species islands and never on 4-species islands

50 Null Model Example He tested four different ‘source pool’ scenarios, varying in the likelihood of occupying habitat categories Together (Schoener and Case), these studies show results will be sensitive to sample size, source pool definitions, and assumptions about the colonization potential of species…and is a good tool for evaluating niche overlap

51 Randomization of Utilization Matrices In most cases, a source pool is not available to generate a biologically realistic community Instead, the observed utilization matrix must be used to estimate overlap values in the absence of competition

52 Lawlor’s Algorithms Four algorithms that vary in the amount of original utilization data is retained in the null community 0 states0 states randomizedretained Obs. utilization from uniform RA1 RA2 distribution Obs. utilizations reshuffled RA 3 RA4

53 Lawlor’s Algorithms RA1: all resource state is possible and equiprobable RA2: resource utilization is randomized, but only for those states that are >0 RA3: observed utilizations are randomly reassigned to different resource categories RA4: only the nonzero resource states in each row are reshuffled

54 Lawlor’s Algorithms RA1: all resource state is possible and equiprobable RA2: resource utilization is randomized, but only for those states that are >0 RA3: observed utilizations are randomly reassigned to different resource categories RA4: only the nonzero resource states in each row are reshuffled

55 Lawlor’s Algorithms RA1: all resource state is possible and equiprobable RA2: resource utilization is randomized, but only for those states that are >0 RA3: observed utilizations are randomly reassigned to different resource categories RA4: only the nonzero resource states in each row are reshuffled

56 Lawlor’s Algorithms RA1: all resource state is possible and equiprobable RA2: resource utilization is randomized, but only for those states that are >0 RA3: observed utilizations are randomly reassigned to different resource categories RA4: only the nonzero resource states in each row are reshuffled

57 RA3: random reassignment Hab AHab BHab CHab D Sp A Sp B Sp C Hab AHab BHab CHab D Sp A Sp B Sp C

58 Lawlor’s Algorithms RA1: all resource state is possible and equiprobable RA2: resource utilization is randomized, but only for those states that are >0 RA3: observed utilizations are randomly reassigned to different resource categories RA4: only the nonzero resource states in each row are reshuffled

59 Hab AHab BHab CHab D Sp A Sp B Sp C Hab AHab BHab CHab D Sp A Sp B Sp C

60 Which one? RA1 is consistent with the idea that competition is so severe that some species are completely denied the use of certain resources by the presence of competitors Conceptually, resource is in its theoretical niche, just not its current realized niche (not recommended by Gotelli and Graves)

61 Which one? RA2 & RA4 (not recommended) ensure that species which do not use certain resource states in nature never do so in a null community RA3 is a compromise by retaining the same number of zero states as the originally observed, but does not constrain those zeros to their original placement


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