BIOS 6150: Ecology Dr. Stephen Malcolm, Department of Biological Sciences

Transcription

1 BIOS 6150: Ecology Dr. Stephen Malcolm, Department of Biological Sciences Week 11: Abundance & Metapopulations. Lecture summary: Based on: Chapters 6 and 7 Begon, Mortimer & Thompson, (1996). Chapters 15 and 23 in Begon, Harper & Townsend (1996). Chapters 6, 14 & 15 in Begon, Townsend & Harper (2006). Population regulation: A.J. Nicholson. H.G. Andrewartha and L.C. Birch. Key-factor analysis & densitydependence. Metapopulations. Ilkka Hanski BIOS 6150: Ecology - Dr. S. Malcolm. Week 11: Abundance & metapopulations Slide - 1

2 2. Explaining distribution and abundance - contrasting views: (1) A.J. Nicholson (1954): Australian. Considered that density-dependent, biotic interactions most influenced population size. (2) H.G. Andrewartha and L.C. Birch (1954): Also Australians. Considered that density-dependent processes: Are... in general, of minor or secondary importance, and... play no part in determining the abundance of some species (from Clark et al., 1967). BIOS 6150: Ecology - Dr. S. Malcolm. Week 11: Abundance & metapopulations Slide - 2

3 3. Nicholson: Governing reaction induced by density change holds populations in a state of balance in their environments,...the mechanism of density governance is almost always intraspecific competition, either amongst animals for a critically important requisite, or amongst natural enemies for which the animals concerned are requisites (Nicholson, 1954). BIOS 6150: Ecology - Dr. S. Malcolm. Week 11: Abundance & metapopulations Slide - 3

4 4. Nicholson - abiotic vs biotic factors: Although he recognized that densityindependent factors like rainfall could influence the level at which densitydependent biotic interactions governed, he considered that densitydependent processes play a key role in regulating populations. BIOS 6150: Ecology - Dr. S. Malcolm. Week 11: Abundance & metapopulations Slide - 4

5 5. Andrewartha & Birch: Numbers of animals limited by: (1) Shortage of resources, (2) Unavailability of these resources in comparison to dispersal abilities, and (3) shortage of time when r is positive Fluctuations caused by weather, predators etc. So they rejected divisions of: density-dependent vs density-independent, or, biotic vs physical factors. BIOS 6150: Ecology - Dr. S. Malcolm. Week 11: Abundance & metapopulations Slide - 5

6 6. Andrewartha & Birch - their thrips example: For nearly 14 years they counted thrips on roses in South Australia and measured local temperatures and rainfall (Fig rd ed.). BIOS 6150: Ecology - Dr. S. Malcolm. Week 11: Abundance & metapopulations Slide - 6

7 7. Andrewartha & Birch analysis: By multiple regression analysis they accounted for 78% of the variance in the yearly peak of thrips numbers in relation to 4 climatic factors: 1. Temperature suitability for development < 31 August. 2. Temperature suitability for development in September & October. 3. Temperature suitability for development in August of the previous season. 4. Rainfall in September & October. Using these data they could predict quite accurately how many thrips would occur in the following year. Concluded that everything was a race against time & densitydependent processes like competition never became important. BIOS 6150: Ecology - Dr. S. Malcolm. Week 11: Abundance & metapopulations Slide - 7

8 8. Problems with interpretation: The interpretation of Andrewartha and Birch could not invoke density-dependence because the regression technique could not detect it: Hides what is going on! Using techniques that can detect density-dependence, the data are clearly density-dependent: (Figs & 6.3). Weather caused density-dependent mortality because refuges from winter weather were limited. Therefore it was not weather but refuges that were density-related. BIOS 6150: Ecology - Dr. S. Malcolm. Week 11: Abundance & metapopulations Slide - 8

9 9. Regulation vs determination of abundance: Regulation of abundance can only occur via density-dependent processes, but abundance can still be determined by the combined effects of all processes that impact a population: Probably includes both densitydependent and density-independent factors. BIOS 6150: Ecology - Dr. S. Malcolm. Week 11: Abundance & metapopulations Slide - 9

10 10. Key-factor analysis: Mostly promoted by George Varley: Used to assess the relative importance of k-values in determining population size By regression of individual k-values against total mortality (K total ). Determines whether separate mortalities vary randomly or vary with the overall mortality (see Tables 14.1, 14.2). k 6 agrees most with k total (Fig. 14.4) and so has the highest regression coefficient in Table But these variables are not independent and so cannot be compared statistically, although this is a measure of relative importance. BIOS 6150: Ecology - Dr. S. Malcolm. Week 11: Abundance & metapopulations Slide - 10

11 11. Density-dependent regulation: Plotting k-values against log population size shows degree of density-dependent population regulation (see Fig. 15.9). b =2.65 for k 6 (Table 14.2, Fig. 15.9a) is >1: Shows overcompensating density-dependent regulation. Inverse density-dependence (Fig. 15.9b). Undercompensating density-dependence (Fig. 15.9c). Based on observed k-values, predictions can be made into the future. BIOS 6150: Ecology - Dr. S. Malcolm. Week 11: Abundance & metapopulations Slide - 11

12 12. Population regulation of wild oats: Density-dependent and density-independent regulation of wild oat plants in monoculture or in competition with wheat (Figs & 6.15). Underlying cause of regulation is intraspecific through reduced seed production at high density (6.14c). But: Interspecific seed predation is also density dependent, and Interspecific competition with wheat (Fig. 6.14a) also shows density-dependent reduction of reproductive rates (Fig. 6.15) which are depressed further by the application of herbicide as a density-independent process. Adult survivorship is density-independent (6.14b). BIOS 6150: Ecology - Dr. S. Malcolm. Week 11: Abundance & metapopulations Slide - 12

13 13. Metapopulations: Most populations are fragmented and patchy. Dispersal among patches with variable dynamics is important. Most populations are subject to repeated episodes of local immigrations and extinctions. BIOS 6150: Ecology - Dr. S. Malcolm. Week 11: Abundance & metapopulations Slide - 13

14 14. Population size: Fragmented populations may remain small because: 1. There are few habitable patches. 2. Habitable sites are small. 3. Habitable sites are far apart: Relative to dispersing ability of the species. 4. Habitable sites support few individuals: Low carrying capacity. 5. Sites are habitable for only short periods of time. 6. Slow population growth after colonization. BIOS 6150: Ecology - Dr. S. Malcolm. Week 11: Abundance & metapopulations Slide - 14

15 15. Development of metapopulation theory: 1. Local populations are linked genetically to form a metapopulation. Population genetics to describe gene flow among populations linked by dispersal. 2. Equilibrium Theory of Island Biogeography of MacArthur & Wilson (1967): Focused on extinction and colonization of species on islands as influenced by their life histories along the continuum between r- selection and K-selection. 3. Levin s model of metapopulation dynamics also published in 1967 described population dynamics at 2 levels: (i) Within patches. (ii) Among patches. BIOS 6150: Ecology - Dr. S. Malcolm. Week 11: Abundance & metapopulations Slide - 15

16 16. Metapopulation persistence: Metapopulation persists stably through balance between: Random extinctions and recolonizations. Even though none of the local populations are stable in their own right (Fig. 7.1 bmt 1996). In addition, the greater the variation in patch size the more likely a metapopulation will persist: An important argument in conservation. With mosaic of source ( donor) and sink ( receiver) patches (Fig. 6.17). BIOS 6150: Ecology - Dr. S. Malcolm. Week 11: Abundance & metapopulations Slide - 16

17 Figure 6.3: N A adults produce N L larvae after k 1 random mortality. (a) k 2 = weakly density dependent, (b) k 2 = strongly density-dependent mortality. Begon, Mortimer & Thompson (1996) BIOS 6150: Ecology - Dr. S. Malcolm. Week 11: Abundance & metapopulations Slide - 17

18 Table 14.1 ( rd ed.): BIOS 6150: Ecology - Dr. S. Malcolm. Week 11: Abundance & metapopulations Slide - 18

19 Table 14.2 ( rd ed.): Slope against k total Slope against log N BIOS 6150: Ecology - Dr. S. Malcolm. Week 11: Abundance & metapopulations Slide - 19

20 Figure 14.4a: Change in Colorado potato beetle k-values with time at 3 sites. BIOS 6150: Ecology - Dr. S. Malcolm. Week 11: Abundance & metapopulations Slide - 20

21 Figure 15.9, 3 rd ed. (14.4b 4 th ed.): Colorado potato beetle mortalities: (a) density-dependent emigration, (b) inversely density-dependent pupal parasitism, (c) density dependent larval starvation. BIOS 6150: Ecology - Dr. S. Malcolm. Week 11: Abundance & metapopulations Slide - 21

22 Figure 6.14: Population regulation in Avena fatua in monoculture or in competition with wheat. Begon, Mortimer & Thompson (1996) BIOS 6150: Ecology - Dr. S. Malcolm. Week 11: Abundance & metapopulations Slide - 22

23 Figure 6.15: Density-dependent & densityindependent regulation in Avena fatua. Begon, Mortimer & Thompson (1996) BIOS 6150: Ecology - Dr. S. Malcolm. Week 11: Abundance & metapopulations Slide - 23

24 Figure 7.1: Probability of local extinction against site occupancy: (a) mangrove island insects, (b) leafhoppers, (c) pond molluscs. Begon, Mortimer & Thompson (1996) BIOS 6150: Ecology - Dr. S. Malcolm. Week 11: Abundance & metapopulations Slide - 24

25 Figure 6.17 (15.22, 3 rd ): Two metapopulations of the silverstudded blue butterfly (a) limestone, (b) heathland (fill: ; open: e = 1983, c = 1990). BIOS 6150: Ecology - Dr. S. Malcolm. Week 11: Abundance & metapopulations Slide - 25