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C O M M O N W E A LT H S E C R E A R I AT M2.2 Life histories and ecological adaptations Assessing the status of fish stock for management: the collection and use of basic fisheries data and statistics 27 November -8 December 2006, University of the South Pacific, Suva, Fiji Islands Content • Life histories, life history traits, trophic levels, species interaction. • The principles of mortality, growth, maturity and their relation to ecological and evolutionary strategies • r versus K selection. Life histories • Life history traits are the underlying determinants for population response to environmental (both biotic and abiotic) forcing. – On top of this natural variation will be a modification of the response due to fishing removals. King and McFarlane (2003) Life histories The perfect organism (fish) would: • • • • Mature early Be large Live long Produce numerous large offspring to start reproducing to avoid predation to produce more to increase offspring and protect each from predation Why is this not possible? Life histories – trade offs If the perfect organism (fish) would: • • • • Mature early Be large Live long Produce numerous large offspring would impede growth take time and energy future predictable many and large at the same time takes too much energy You have to „choose‟ a strategy Egg size - fecundity • Many small eggs • Few large eggs • Live-born young Fecundity Fecundity Relative fecundity • Fecundity increases exponentially with length. If fecundity increases faster than weight then relative fecundity also increases with size. Frequency distributions of age-of-maturity, clutch size, egg diameter and parental care for marine and fresh water fish species Winemiller & Rose (1992) Life history and environment Dying is more certain than giving birth! Most ecological processes and life history traits can be related to the prevailing mortality pattern: • The unstable environment: characterised by discrete, density independent, non-predictive, nonselective mortality induced by physical changes • The stable environment: characterised by continuous, density-dependent, predictive, and sizeselective mortality induced by the biotic community. Mean size of organisms Cope‟s rule Stable period Stable period Stable period Stable period Geological time Cope's rule states that evolution tends to increase body size over geological time in a lineage of populations. But the precondition is geological stability. During unstable periods with mass extinction the large lineages are more susceptible. Investment in age (size) is investment in future. Predator or prey? Predation mortality Instantaneous predation mortality (M2) on Cod by other species in the North Sea Modified from ICES (1997). Life history „trade offs‟ Blueweiss et al. (1978) The intrinsic rate of natural increase: r = 0.025 ∙ Wmax-0.26 Life history „trade offs‟ Modified from Banse & Mosher (1980) Log P/B ratio is a linear function of log body size Life history invariants = constant trade off between traits Examples of Invariants • – Ratio of lifespan (E) to age-at-first reproduction (a) This ratios is similar for elephant and squirrels, but different from fish (Charnov et al. 2001. Proc. Nat. Acad. Of Sci. 98:9460-9464) Jensen (1997, CJFAS 54:987-989) Proposed the following invariants • 1. Natural mortality (M) and age at maturation (Tm) M∙Tm = 1.65 • 2. Natural mortality (M) and VBGF „coefficient‟ (K) M = 1.5 K • 3. Length at maturity [ Lm ] and maximum length (L∞) Lm = 0.66 L∞ • 4. Growth „coefficient‟ (K) and maximum length (L∞) L∞ = K-0.33 Life history strategies Environment seasonal or with large scaled spatial variation Fecundity Environment unstable or with large scaled spatial variation Periodic Opportunistic Age of Maturity r-selection K-selection Equilibrium Winemiller & Rose (1992) Environment stable with fine scaled spatial variation Life history strategies Winemiller (2005) Phylogentic life history variables • • • • • • • • • growth rate (K, yr-1 and L∞, cm) max size (Lmax, cm) and max age (Tmax, years) age at maturity (Tm, years) length at maturity (Lm, cm) length-at-5%-survival (L.05, cm) time-to-5%-survival (T.05, years) slope of the log-log fecundity-length relationship (Fb) fecundity the year of maturity (Fm) egg size (mm) • egg volume (egg, mm3) Life histories: The phylogenetic comparative approach Winemiller & Rose (1992), McCann & Shuter(1997) Life History Strategies 1. Opportunistic strategists fast-growing; short-lived; intermediate fecundity 2. Periodic strategists slow-growing, long-lived, high fecundity 3. Equilibrium strategists fast-growing, long-lived, low fecundity 4. Salmonic strategists opportunistic strategists but with freshwater and marine phase King and McFarlane 2003 Principal Components Analysis (PCA) on life history traits King and McFarlane 2003 PCA groups on life history traits King and McFarlane 2003 Typical population dynamics Opportunistic strategist King and McFarlane 2003 Typical population dynamics Periodic strategist King and McFarlane 2003 Typical population dynamics Equilibrium strategist King and McFarlane 2003 r-K selection • r-selected species: – Small – Rapid growth – Early maturation – No parental care – Opportunistic – Colonisers – Unstable environment – Resilient • K-selected species – Large – Slow growth – Late maturation – Parental care – Specialised – Competitors – Stable environment – Vulnerable Logistic growth: r-K selection Carrying capacity = B∞ = K K 2 dB dt r B dB dt B r B1 K Equilibrium Periodic Opportunistic Winemiller (2005) Population dynamics in relation to carrying capacity and the relative strength and frequency of density dependence for three life history strategies Life history traits at the community level Increased mortality has different impact depending on the trophic level. Traits that make species vulnerable covary both between and within trophic levels. Body size (size of the circles) of top carnivore species tends to be larger than that of species at lower trophic levels. Range of body sizes and number of species are larger at lower trophic levels. From Raffaelli (2004) Life history and communities • Traits such as body size and its covariates such as home range and tolerance to stress, together with differences in species richness between trophic levels, will determine the impact on ecosystems of different biodiversity loss scenarios: • Top predators with their large body size, low abundance, and large range requirements are particularly vulnerable to habitat fragmentation or destruction, but less susceptible to pollution stress, which affects smaller species disproportionately. • In contrast, the higher species richness at lower trophic levels, provides more “insurance” against the effects of species losses. These species also have greater capacity for adaptive change due to their shorter life-spans and faster turnover rates. • With respect to species traits, extinction is unlikely to occur randomly. Raffaelli (2004) The r-K selection principle as a function of mortality pattern Abundance (Log N) Increased juvenile mortality = K-selection Slope = total mortality rate Z = r Increased adult mortality = r-selection Age (size) Kolding (1993) K-selection: Stable environment, biotic mortality (predation) – predictive, size selective r-selection: Unstable environment, abiotic mortality – non-predictive, non-selective The biomass-size distribution Biomass A Lindeman pyramid illustrating a fish community. Size The biomass-size distribution is an important indicator in both single species and community studies. Changes in intercept is informative about changes in biomass While changes in slope is informative about mortality pattern Biomass-size distributions in different environments Detrivores, Herbivores, Zooplanktivores, Macro-invertebrate feeders Piscivores Energy A Competition Predation Constant systems Biomass B Biomass-size distributions: Slope = Z = r = P/B Pulsed systems Size of individual fish Fishing pressure „Production‟ = Z∙ Biomass = area ∙ slope Trophic interactions: Top down versus Bottom up control. Cascading effects Response of zooplankton and phytoplankton community biomass to: - fish (top down) - nutrient (bottom up) - combined treatments (N = 11). Brett & Goldman 1997 Predator-prey relationships: Cascading effects Predator-preys often have time lagged oscillations due to density dependent responses. Left Fig:Dynamics of shrimp and cod biomass in the Barents Sea from 1982-1998. Berenboim et al. 2000 J. Northw. Atl. Fish. Sci., Vol. 27 Predator-prey relationships: Cascading effects Inverse biomass trends as an illustration of a trophic cascade in the Black Sea (from Daskalov 2002) Final comments • Life histories are evolved and shaped by different mortality patterns • Mortality due to environmental variations and habitat destructions are typically discrete, nonselective, non predictive, and increase mortality on all size groups. • Mortality due to predation is typically continuous, highly selective, predictive, and predominantly affects young and small individuals. Predation and fishing on cod Man is selecting opposite all other predators!! From ICES (1997).