BIOL 203 Lecture 13 Population Dynamics Fall 2024 PDF

Lecture 13 Population dynamics over time and space BIOL 203 November 15th, 2024 1 Learning objectives 1. Recognize that population size fluctuates naturally over time 2. Explain how density dependence with time delays can cause populat...

Lecture 13 Population dynamics over time and space BIOL 203 November 15th, 2024 1 Learning objectives 1. Recognize that population size fluctuates naturally over time 2. Explain how density dependence with time delays can cause population size to be inherently cyclic 3. Describe how chance events can cause small populations to go extinct 4. Illustrate how metapopulations are composed of subpopulations that experience independent population dynamics 2  Population size Key Concept fluctuates naturally over time 3 Population size fluctuates naturally over time All populations experience fluctuations in size over time Population dynamics = variation in population size over time or space Can be relatively stable or widely fluctuating Differences in body size, population response time, and sensitivity to environmental change affect population dynamics 8 Population size fluctuates naturally over time Small organisms (e.g., algae) can reproduce very quickly (hours), so populations can respond very quickly to environmental conditions High surface-area-to-volume ratio means they are more sensitive to changes as well 9 Population size fluctuates naturally over time Larger, longer-lived species have longer generation times, population includes many age classes Year to year fluctuation in birth rates have less impact Also maintain homeostasis easier (less sensitive to environmental conditions) 10 Fluctuations in age structure Age structure can fluctuate If a certain age group contains unusually high/low numbers of individuals, suggests that population experienced unusually high birth or death rates in past E.g.) whitefish (Coregonus clupeaformis) 11 Overshoots and die-offs Populations can often temporarily exceed carrying capacity = overshoot Can occur when carrying capacity decreases year over year Will experiences a die-off = substantial decline in population density Typically goes well below carrying capacity 12 Overshoots and die-offs E.g.) Reindeer on St. Paul Island 25 individuals introduced in 1911 Exponential growth then massive die-off in 1938 Now maintained at ~400 individuals 13 Concept check What is the relationship between a species lifespan and the degree to which their population size fluctuates over time? What are causes of population overshoots and die-offs? 14  Density dependence Key Concept with time delays can cause population size to be inherently cyclic 15 Density dependence with time delays can cause population size to be inherently cyclic Some populations experience regular patterns of population fluctuations = population cycles E.g.) Gyrfalcon Exports match natural population cycles 16 The cycling of populations around their carrying capacity Populations are a like a pendulum; fluctuates above/below carrying capacity At carrying capacity, populations are stable When population decreases (predation, disease, etc.), the population starts to grow If growth is rapid, can grow beyond carrying capacity; results in die-off Caused by delay between initiation of breeding and time that offspring added to population 18 Delayed density dependence Delayed density dependence = when density dependence occurs based on a population density at some time in the past Can be caused by several factors relating to carrying capacity E.g.) Long gestation periods – moose breed in fall but don’t give birth in spring, available resources (K) could be different by then E.g.) Predators increase reproduction when prey abundant, could decrease by the time offspring born 19 Modelling delayed density dependence Delayed density dependence can be modelled with a modified form of the logistic growth model equation: 𝑑𝑁 𝑁𝑡−𝜏 = 𝑟𝑁 1 − 𝑑𝑡 𝐾 Where: τ = time delay Nt-τ = population size in the past 20 Modelling delayed density dependence Whether a population cycles above/below carrying capacity depends on the magnitude of the time delay (τ) and the magnitude of the intrinsic growth rate (r) As time delay increases, density dependence is further delayed, population is more prone to overshooting/undershooting carrying capacity High intrinsic growth rate also increases chance of overshoot 21 Modelling delayed density dependence The amount of cycling a population experiences depends on the product of r and τ When low (rτ < 0.37), no oscillations 22 Modelling delayed density dependence The amount of cycling a population experiences depends on the product of r and τ When intermediate (0.37 < rτ < 1.57) = damped oscillations Population growth initially oscillates, magnitude of the oscillations declines over time 23 Modelling delayed density dependence The amount of cycling a population experiences depends on the product of r and τ When high (rτ > 1.57) = stable limit cycle Population size continues to exhibit large oscillations over time 24 Population sizes cycle in laboratory populations E.g.) Daphnia galeata When population is low and abundance of food, individuals store excess food as lipid droplets Growing population depletes resources, still reproduce because of stored lipid droplets; can pass to offspring Causes populations to overshoot, then die- off 25 Population sizes cycle in laboratory populations E.g.) Bosmina longirostris Do not store as many lipid droplets, no energy buffer against reduction in food, cannot reproduce beyond carrying capacity 26 Concept check Why does delayed density dependence cause population size to cycle? How do we adjust the logistic growth model to account for delayed density dependence? 27  Chance events can Key Concept cause small populations to go extinct 28 Chance events can cause small populations to go extinct When populations are large, density-dependent factors cause slower growth When populations are small, density-dependent factors cause faster growth Since growth rate often dictated by population size, how do we get populations going extinct? Relationship between population size and probability of extinction 29 Extinction in small populations Small populations are more vulnerable to extinction than large populations More vulnerable to density independent factors (e.g. natural disasters) and density-dependent factors (Allee effects) 30 Extinction in small populations E.g.) Birds in the Channel Islands Counted breeding pairs over 80 year period Greater extinction rates seen on smaller islands 31 Extinction in small populations Small populations of plants are also vulnerable to extinction E.g.) Plant populations in Germany Sampled populations over 10 years Smaller populations more likely to go extinct 32 Extinction due to variation in population growth rates Density-dependent population models show that small populations grow more rapidly than larger populations But small populations more likely to go extinct Why don’t they recover? 33 Extinction due to variation in population growth rates So far, we have assumed single birth/date rate for each individual in a population Deterministic model = designed to predict result without accounting for random variation in population growth rate Simpler but less realistic 34 Extinction due to variation in population growth rates Stochastic models incorporate random variation in population growth rates Two types of variation: Demographic stochasticity = random variation in birth/death rates due to differences among individuals Environmental stochasticity = variation is due to changes in environmental conditions (e.g., weather, natural disasters) 35 Extinction due to variation in population growth rates Stochastic models look at average growth rate with variation around average Rather than fixed growth rate, population experiences range of growth rates If population experiences many above average growth years in a row, grows rapidly If population experiences many below average growth years in a row, slower growth Outcome determined by chance 36 Extinction due to variation in population growth rates Probability of extinction decreases in larger populations 37 Concept check What is the relationship between population size and the probability of extinction? What is the difference in approach between deterministic and stochastic population growth models? What is the difference between demographic and environmental stochasticity? 38  Metapopulations are composed of Key Concept subpopulations that experience independent population dynamics 39 Metapopulations are composed of subpopulations Population dynamics also vary over space Populations are often divided into subpopulations = smaller groups of conspecifics that live in isolated patches Infrequent dispersal among subpopulations, dynamics are independent Collection of subpopulations = metapopulation 40 The fragmented nature of habitats Metapopulations can occur when habitat is naturally patchy E.g.) Wetlands in North America Terrestrial habitat often inhospitable, minimal dispersal between water bodies 41 The fragmented nature of habitats Metapopulations can also occur due to human activities Habitat fragmentation = breaking up of large habitats into a number of smaller habitats 42 Conceptual models of spatial structure Three models for spatial structure of subpopulations: Basic metapopulation model Source-sink metapopulation model Landscape metapopulation model 43 The basic metapopulation model The basic metapopulation model describes a scenario in which there are patches of suitable habitat embedded within a matrix of unsuitable habitat 44 The basic metapopulation model All suitable patches equal quality Some patches occupied, others not Unoccupied patches can be colonized by dispersers Emphasizes how colonization/extinction events affect proportion of occupied suitable habitats 45 The source-sink metapopulation model The source-sink metapopulation model builds on basic model but includes variation in patch quality Source subpopulations = high-quality habitats, dispersers in metapopulations Sink subpopulations = low-quality habitats, outside dispersers maintain subpopulation 46 The landscape metapopulation model The landscape metapopulation model builds on the source-sink model by including variation in the unsuitable habitat surrounding patches 47 The basic dynamics of metapopulations We will use the basic model Proportion of Assume habitat patches equal quality, same occupied patches subpopulation size, equal number of dispersers at equilibrium Some fraction of habitats will be occupied (p) 𝒆 ෝ =𝟏− 𝒑 Fixed probability that a patch becomes 𝒄 unoccupied through extinction (e) Fixed probability of colonization (c) 48 The basic dynamics of metapopulations Basic model indicates how we could increase the number of occupied habitats (also increasing Proportion of population size) occupied patches at equilibrium Increasing colonization (e.g., habitat corridors) 𝒆 Decrease extinction (e.g., improve habitat ෝ =𝟏− 𝒑 quality) 𝒄 49 Observing metapopulation dynamics in nature Do we see a balance of colonization/extinction rates in nature? E.g.) Glanville fritillary butterfly (Melitaea cinxia) Lives in isolated patches of dry meadows Monitored extinction/colonization of 1600 patches; 12-39% occupied, over 9-year period, ~100 colonized and ~100 extinct 50 Observing metapopulation dynamics in nature Determined that no patch is safe from extinction, but metapopulation supports all patches 51 Patch size and isolation Habitat patches are rarely equal in quality Larger patches typically support more individuals (more resources) E.g.) California spotted owl (Strix occidentalis occidentalis) 52 Patch size and isolation When patches can support differing number of individuals, we expect smaller patches to experience higher rates of extinctions Leads to fewer small patches occupied than large patches Distant patches will also have a lower chance of being occupied than close patches Less isolated patches could be supported/saved from extinction by nearby dispersers = rescue effect 53 Patch size and isolation E.g.) The effect of patch size/isolation on occupancy in skipper butterflies (Hesperia comma) Patches range from 0.01-10 ha Distance ranges from 0.02-100 km Largest, least isolated more most likely to be occupied 54 Concept check What reality do the source-sink and landscape metapopulation models involve that the basic metapopulation does not? How do patch size and distance between patches affect the rate of patch colonization? 55 Next class Predation and herbivory (Chapter 13) Seminar: Community interactions Poster presentations: week of Nov. 25th 56