ANT 154B Course notes- Lecture _12

ANT 154B Course notes- Lecture _12 - ANT 154BN Course notes...

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Unformatted text preview: ANT 154BN Course notes Lecture #12: Abundance and rarity 15 February 2011 Key terms and concepts are indicated in blue Outline 1. Population ecology 101 2. Population dynamics 101 3. Measuring primate abundance 4. What determines primate abundance? 1. Population ecology 101 Population: a group of interbreeding individuals easy to define, hard to delineate in the field, especially without geographic boundaries Principle goals of population ecology Individual characteristics –> Population characteristics Population growth models Individual processes –> Population processes N = population size Population growth models Population growth models N = population size Nt+1 = Nt + b + i - d - e b = births d = deaths i = immigration e = emigration Tuesday, February 16, 2010 Nt +: births, immigration -: deaths, emigration Nt+1 Nt+1 Tuesday, February 16, 2010 = Nt + b +X - d -X i e 9 (assume closed population) Nt+1 = Nt + b - d dN dt dN dt = (b-d)N = rN r = population growth rate 10 (aka, intrinsic rate of increase) 11 Tuesday, February 16, 2010 o f total annual precipitation o f m e a n precipitation in wettest m o n t h o f m e a n precipitation in driest m o n t h ANT 154B Lecture #12 course notes AN.CV.ppt HI.CV.ppt LO.CV.ppt page 2 of 7 Population growth when resources unlimited high rmax population size es o f intra-year variability o f temperature within the y e a r MNTH.CV. t V m e a n m o n t hry tpopulation growth rate (aka, intrinsic rate of increase) l = emps). o f ppt. within the y e a r MNTH.CV.ppt V m e a n m o n t hrmax recipitation). rate of population growth l y p = = maximum coefficient o f v a r i a t i o n Primate relative rmax varies moderate rmax low rmax might comthese varilatitude and ecies within e variation n o f species s that may alysis a t the n in relative values, b u t y d a t a were alyses were maller taxecies within 0.08 E 0.04 Tuesday, February 16, 2010 time 13 t- o.oo -0.04 -0.08 1 2 3 4 5 Habitat group Fig. 1. H a b i t a t type a n d mean relative rm f o r 72 primate species, where relative r m = o b s e r v e d log10 rm-expected loglo r,,. Habitat grous: / = s p e c i e s restricted t o o r preferring p r i m a r y forest; 2 = forest species n o t restricted t o p r i m a r y forest; 3 = species restricted t o o r preferring s e c o n d a r y a n d edge forest; 4 = w o o d l a n d species; 5 = species f o u n d in highly seasonal habitats t habitats each habe n t h e rm the relaT h e relae seen in ts have a are f o u n d f o r their hich are habitats ifferences s t h e difb e signifion o f the d a t a reveal t h a t f o r t h e " p r i m a r y f o r e s t " species o n l y one, a p o s i t i vresources are limited e r e l a t i v e rm, h a v iresources are e s t r e l a t i v e v a l u e o f a l l o f t h e n g t h e h i g h limited But 7 2 s p e c i e s . I f t h e a n a l y s i s i s r e p e a t e d w i t h o u t t h i s s p e c i e s , population growth rates slow down as N -> K t h e r e is a s i g n i f i c a n t d i f f e r e n c e b e t w e e n t h e g r o u p s ( A N O V A , F - t e s t P = 0.042). P r i m a r y f o r e s t species ( h a b population size i t a t g r o u p 1) a r e f o u n d t o h a vK a s i g n i f i c a n t l y l o w e rpopulation size e K r e l a t i v e r,~ t h a n e i t h e r e d g e s p e c i e s ( h a b i t a t 3 ) o r s p e c i e s sigmoidal curve of logistic i n t h e m o s t s e a s o n a l h a b i t a t s ( h a b i t a t 5) ( P < 0 . 0 5 ) . T h e population growth g e n e r a l f o r e s t s p e c i e s ( g r o u p 2) a r e a l s o f o u n d t o h a v e a l o w e r r e l a t i v e rm t h a n s p e c i e s i n t h e m o s t s e a s o n a l h a b time i t a t s ( h a b i t a t 5) ( P < 0 . 0 5 ) . time W i t h i n s m a l l e r t a x o n o m i c g r o u p i n g s (i.e. s u b o r d e r s , families, s u b f a m i l i e s , g e n e r a ) v e r y few s i g n i f i c a n t diff e r e n c e s c o u l d b e f o u n d b e t w e e n r e l a t i v e rm v a l u e s o f K-N species in different h a b i t a t s . dN (= carrying capacity) Tuesday, February 16, 2010 Population d l e m u when a r e c i a v aunlimited, but... t h e r u f f e growth r ( V resources r i e g a t u s ) , h a s 16 Tuesday, February 16, 2010 15 dt = rN ( K ) ( K-N K ) N is small (well below K) ~ 1 as N -> K ~ 0 Tuesday, February 16, 2010 17 ANT 154B Lecture #12 course notes page 3 of 7 Life history strategies population size R vs. K. K “K” species “r” species time r -strategists 18 K -strategists offspring larger, stronger/more protected mature & reproduce slowly inhabit stable environments long lifespan 19 Tuesday, February 16, 2010 offspring smaller, weaker/ vulnerable mature & reproduce rapidly inhabit unstable environments short lifespan Tuesday, February 16, 2010 19 2. Population dynamics 101 K strategists experience less extreme population fluctuations K strategists experience less extreme population fluctuations boom boom bust N K fairly stable N time K strategists time r strategists Tuesday, February 16, 2010 24 Regulatory forces have density-dependent effects around K Population dynamics 101: regulation Population dynamics 101: regulation dN dt = rN ( K-N K ) N K Regulatory forces are mechanisms that: N<K dN dt dN dt 27 populations grow regulating forces N>K populations decline // time Tuesday, February 16, 2010 Regulatory forces have density-dependent effects around K Tuesday, February 16, 2010 26 ANT 154B Lecture #12 course notes Effects of limiting forces ~ density-independent Population dynamics 101: limitation page 4 of 7 N K limiting forces 454 / Marshall et al. 454 / Marshall et al. (a) (a) time Effects of limiting forces ~ density-independent Tuesday, February 16, 2010 29 Line transect methods 0 Number of observations // Number of observations 0 3. Measuring primate abundance Line transect methods Distance from transect (b) (b) Distance from transect 0 Number of observations 0 Number of observations Distance from transect (c) Distance from transect (c) Number of observations Direst observations: Number of observations Line transect methods: direct observations Tuesday, February 16, 2010 Fig. 2. Diagram of the effect of visibility on density estimation: (a) 100% visibility (i.e. strip transect, dashed lines); (b) visibility declining with distance from transect; (c) poor visibility with individuals missed on the transect. Left: locations of groups seen (J) or missed (). Right: effect of missed groups on histograms and detection functions. Shaded areas: (b) and (c), number of groups estimated to be missed; hatched area: (c), underestimation caused by individuals missed on the transect. 0 Fig. 2. Diagram of the effect of visibility on density estimation: (a) 100% visibility (i.e. strip transect, dashed lines); (b) visibility declining with distance from transect; (c) poor visibility with individuals missed on the transect. Left: locations from transect (J) or missed (). Distance of groups seen Right: effect of missed groups on histograms and detection functions. Shaded areas: (b) and (c), number of groups estimated to be missed; hatched area: (c), underestimation caused by individuals missed on the transect. Center of group (accurate estimate) 0 Marshall, Lovett & White 2008 Distance from transect 33 impractical for low densities. For example, in Mkungusi (lowland Udzungwa), only one group of red colobus, Procolobus gordonorum, was seen in 40 km of for low densities. Marshall et al., impractical walking [Marshall, 2007;For example, in submitted]. This would require 1,600 km to reach 40 Mkungusi (lowland Udzungwa), only one group of observations. Fewer sightings may, however, be used red colobus, Procolobus gordonorum, was seen in based on common sense and experience [e.g. 15–30 40observations; Peres, 1999]. km of walking [Marshall, 2007; Marshall et al., submitted]. This on or near the 1,600 kmshould be 40 (f) Objects would require transect to reach observations. Fewer sightings may, however,100%, detected with certainty. Where visibility is be used based on common sense andwith distance [e.g. 2a). observations do not decrease experience (Fig. 15–30 observations; Peres, 1999]. (f) Objects on or near the transect should be detected with certainty. Where visibility is 100%, Am. J. Primatol. observations do not decrease with distance (Fig. 2a). More typically, visibility and the number of observations decline with distance (Fig. 2b). If visibility/ detectability is reduced such that groups are missed on the transect line,visibility and the number of observaMore typically, the histogram bars and curve decrease, thus underestimating density (Fig. 2c). In tions decline with distance (Fig. 2b). If visibility/ dense habitats, such as tropical forests,groupsis a missed detectability is reduced such that there are high chance that individuals are missed on the on the transect line, the histogram bars and curve transect. Groups are therefore the more popular decrease, they are less likely to be missed. sample unit asthus underestimating density (Fig. 2c). In dense habitats, such as be exact. forests, there is a (g) Measurements should tropical Estimating high visually may lead to overestimates in distances chance that individuals are missed on the Am. J. Primatol. Edge of group (overestimate) transect. Groups are therefore the more popular sample unit as they are less likely to be missed. (g) Measurements should be exact. Estimating distances visually may lead to overestimates in Marshall, Lovett & White 2008 Tuesday, February (e.g., Indirect observations:16, 2010 nest transects) 34 Limitations of traditional nest transects costly, time consuming ––> limited coverage variable, uncertain parameters ––> limited accuracy and precision ANT 154B Lecture #12 course notes Nest decay rates are highly variable both among and within sites page 5 of 7 Inaccurate nest decomposition rates can have large effects on population estimates At least 6 months needed to establish reliable decay time estimate Need substantial survey effort to obtain a reliable density estimate Matrix method Marked recount method ANT 154B Lecture #12 course notes Ill suited to be rapid survey techniques page 6 of 7 Potential alternative methods Helicopter surveys Remote sensing Mark-recapture (genetic) Structured village surveys 4. What determines primate abundance? How does food limit population density? opinions vary Summary: I Gibbons Leaf monkeys Total food Fallback foods Marshall, Boyko, Feilen, Boyko, & Leighton 2009 Tuesday, February 16, 2010 66 ANT 154B Lecture #12 course notes Summary: II Gibbons Leaf monkeys page 7 of 7 Preferred food (stem density) Preferred food (phenological measure) Take home messages Tuesday, February 16, 2010 Marshall, Boyko, Feilen, Boyko, & Leighton 2009 67 1. Population ecology links individual characteristics and processes to population characteristics and processes. 2. Density-dependent factors can regulate populations, density independent factors limit them. 3. Most primate populations are relatively stable over time, although they are subject to both densitydependent and density-independent factors. 4. Each survey method has associated strengths, limitations, and assumptions. Selection of a survey technique depends on the goals of the survey. 5. Food may be a key limiting (but rarely regulating) factor for primates, but species are affected in different ways by different types of foods (e.g., gibbon vs. leaf monkey example). Question to ponder Imagine you are trying to manage a patch of forest to increase K (carrying capacity) for a particular primate species. Based on your understanding of primate feeding behavior, population ecology, and life history, explain the factors you would consider in deciding what set of plant species to plant in the forest patch. In your answer, be sure to discuss the particular phenological characteristics that your chosen plants would exhibit and how this might depend on the life history and population biology of the species that you are hoping to manage. ...
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