Environmental Stochasticity

Climate change is perhaps the most pressing and urgent environmental issue facing the world today. Despite the

0.0 0.2 0.4 0.6 Plant density (individuals cm-2)
5 10 15 Larval density (individuals cm-2)

20 60 100 Spawner abundance (eggs m-2)

20 60 100 Spawner abundance (eggs m-2)

0 10 30 50 Number of pairs
10 15 20 25 Density (individuals per hectare)

4.95

4.85

4.95

4.85

300 500

300 500

Figure 2 Example patterns of fecundity fertility with changes in population density for (a) scentless chamomile (Tripleurospermum perforatum); (b) midge (Chironomus riparius); (c) brown trout (Salmo trutta); (d) muted swan (Cygnus olor); (e) European rabbit (Oryctolagus cuniculus); and (f) moose (Alcesalces). (a) Reproduced from Buckley YM, Hinz HL, Matthies D, and Rees M (2001) Interactions between density-dependent processes, population dynamics and control of an invasive plant species, Tripleurospermum perforatum (scentless chamomile). Ecology Letters 4: 551-558. (b) Reproduced from Hooper HL, Sibly RM, Hutchinson TH, and Maund SJ. (2003) The influence of larval density, food availability and habitat longevity on the life history and population growth rate of the midge Chironomus riparius. Oikos 102(3): 515-524. (c) Reproduced from Myers RA (2001) ICES Journal of Marine Science 58:937-951. (d) Reproduced from Nummi P and Saari L (2003) Density-dependent decline of breeding success in an introduced, increasing mute swan Cygus olor population. Journal of Avian Biology 34 (1): 105-111. (e) Reproduced from Rodel H, Bora A, Kaiser J, etal. (2004) Density-dependent reproduction in the European rabbit: A consequence of individual response and age-dependent reproductive performance. Oikos 104 (3): 529-539. (f) Reproduced from Solberg EJ, Saether B-E, Strand O, Loison A (1999) Dynamics of a harvested moose population in a variable environment. Journal of Animal Ecology 68 (1): 186-204.

limitations in our ability to predict and quantify the consequences of this change, there is ample evidence that changes in climate have profound effects on the bios. Indeed, given that fertility is one of the key life-history parameters determining population abundance and persistence, it is important to understand how it responds to environmental stochasticity. Prevailing environmental conditions can affect fertility in four principal ways by altering (1) maternal body condition, (2) maternal survival, (3) offspring body condition, and (4) offspring survival. However, quantifying these effects can be challenging. The usual way of collecting such information on vital rate variability is to census a population in different age classes or stages over time and to compare measured vital rates (e.g., fertility) against some environmental variable (see Figure 3 for examples). Although repeated measures provide estimates of temporal variance in vital rates, this total variance also includes two other sources: demographic stochasticity and measurement/ sampling error. The true variance due to environmental stochasticity must be isolated from other sources of variability or risks of decline and extinction may be biased. Several methods exist for partitioning these variances for fertility to examine the role of environmental stochasti-city on this life-history parameter within population models (see also the section titled 'Fecundity and fertility in population dynamical models').

Sex-Allocation Theory

Although sex ratios are discussed elsewhere in this encyclopedia, it is important to understand the basics of sex-allocation theory with respect to fecundity. The discussions centered on the allocation of resources toward reproduction have thus far ignored the notion that the long-term value of producing offspring of one sex versus another depends on the complex relationship between current and future reproduction. Just as various life-history strategies have evolved with respect to the timing, frequency, and magnitude of reproductive effort, there are various optimality models that exist to explain sex ratio variation. Early theoretical work argued that equal sex ratios are evolutionarily stable because parental investment in sons and daughters should be identical under stable environmental conditions and population-wide random mating. However, skewed sex ratios are commonly observed due to factors such as nutritional

w 40

w 40

1950

1970 Year

1990

1950

1970 Year

1990

3 300

3 300

1950

1970 Year

1990

1950

1970 Year

1990

"O

"O

1986

1990 Year

1994

1986

1990 Year

1994

Figure 3 Examples of fecundity fertility measures fluctuating with environmental stochasticity. (a) Breeding success (% chicks fledged of eggs laid) of emperor penguin (Aptenodytes forsteri) pairs from 1952 to 1999. Variation in breeding success increased progressively since the 1970s resulting from complete or extensive breeding failures in some years due to early breakout of the sea ice (b) or from prolonged blizzards during the early chick-rearing period. (c) Breeding success (% chicks fledged of eggs laid) of blue petrel (Halobaena caerulea) pairs from 1985 to 1996. (d) Spearman's rank correlation coefficients between sea surface temperature (SST) anomalies and blue petrel breeding success for the period ranging from February preceding the reproductive period until May the following year. Months where the correlation was nonzero are indicated by an asterisk (*). (a) Reproduced from Barbraud C and Weimerskirch H (2001) Emperor penguins and climate change. Nature 411:183-186. (c) From Inchausti P, Guinet C, Koudil M, Durbec J-P, etal. (2003) Inter-annual variability in the breeding performance of seabirds in relation to oceanographic anomalies that affect the Crozet and the Kerguelen sectors of the Southern Ocean. Journal of Avian Biology 34(2): 170-176.

stress, age, condition, and social rank of mothers, litter size, population density, and changes in resource availability. Optimality models focus on the idea that parents should adjust the sex ratio of their offspring in response to factors affecting their own and their offspring's future reproductive success. For example, one highly cited model used to explain sex ratio variation in mammals predicts that in polygynous species with marked sexual dimorphism, good-condition mothers should invest in the sex showing the highest variation in reproductive success because investment in that sex can potentially provide a better lifetime return on maternal investment. The apparent contradiction to the evolutionary stability of equal sex ratios invoked by adaptive sex ratio manipulation models may be explained by the existence of negative temporal autocorrelation in sex ratios between breeding events over the lifetime of the individual. In other words, equal investment in the sexes may only operate when taking total lifetime reproductive output into consideration.

Project Earth Conservation

Project Earth Conservation

Get All The Support And Guidance You Need To Be A Success At Helping Save The Earth. This Book Is One Of The Most Valuable Resources In The World When It Comes To How To Recycle to Create a Better Future for Our Children.

Get My Free Ebook


Post a comment