Metapopulation Dynamics and Landscape Ecology

Metapopulation Dynamics and Landscape Ecology

Introduction

  • Focus on understanding life history strategies organisms adapt to cope with environments.

  • Interested in environmental change and strategies organisms use to persist.

Module Four Overview

  • Metapopulations: Understanding how these populations work.

  • Incidence Functions: Building on classic models to incorporate ecological realism.

  • Source and Sync Dynamics: Conservation perspective and spatial planning of reserve networks.

  • Holistic View: Relax assumptions of metapopulation models to think about landscapes as a whole.

Habitat Loss and Fragmentation

  • Habitat clearing causes fragmentation, affecting animals restricted to smaller patches.

  • Fragmentation effects manifest most in regions with low habitat and species with low dispersal capabilities.

Metapopulations Defined

  • Collection of local populations in habitat patches that allow movement between them.

  • Important for conserving species in fragmented landscapes and planning natural reserves.

  • Levins defined it as a population of smaller subpopulations, highlighting local extinctions and recolonizations.

Classical vs. Metapopulation Theory

  • Classical ecology tracks species abundance based on births and deaths.

  • Metapopulation theory considers open subpopulations and dispersal importance for persistence.

  • Metapopulations involves inputs through births and immigration and outputs through deaths and immigration.

Metapopulation Dynamics

  • Landscape represents suitable habitat; unsuitable matrix restricts establishment.

  • Colonization events increase white dots; local extinctions turn white dots red.

  • At a regional scale, the metapopulation persists despite local extinctions.

Key Concepts

  • Metapopulation: Assemblage of local populations interacting via dispersal.

  • Persistence achieved: Balancing local extinctions through recolonization events.

  • Suitable Habitat Patches: Can be unoccupied; doesn't mean unsuitable

  • Patch Matrix View: Suitable habitat patches in a matrix of unsuitable landscape.

Modeling Dynamics

  • Simple snapshot data on patch occupancy allows modeling.

  • Easy-to-test theories with real-world data.

Benefits of Metapopulations

  • Likelihood of regional persistence increases with the number of local populations.

  • Spreading of risk: XX is number of subpopulations within the metapopulation decreases the probability that the metapopulation at the regional scale is going to go extinct.

Early Models

  • Classic model proposed by Levins.

  • PP = proportion of occupied patches.

  • 1−P1 - P = proportion of empty patches.

  • CC = colonization rate.

  • EE = extinctions.

  • Models change in the proportion of occupied habitats over time.

Equilibrium

  • Phat=1−ECP_{hat} = 1 - \frac{E}{C}

  • Metapopulation persists if the colonization rate exceeds the extinction rate.

Levens-Type Models

  • Rate of change in the proportion of occupied patches = colonizations - extinctions.

  • Colonization Rate: Proportion of unoccupied sites that become occupied per unit time.

  • Extinction Rate: Proportion of occupied sites that go extinct in the next time step.

Scenarios for Colonization Rate

  • Constant Function Colonization: Not influenced by other occupied patches.

  • Linear Increase Colonization: Probability increases as more sites are occupied.

Island Mainland Metapopulation

  • Colonization rate is not influenced by occupied patches.

  • Mainland acts as a source of colonists dispersing equally to smaller populations.

Closed Metapopulation

  • Colonization rate increases as other patches become occupied.

  • Dependent on the proportion of occupied sites.

Propagule Rain Effect

  • Stream of colonists from the mainland.

  • Flat line indicates propagule rain effect in this system.

Extinction

  • Island mainland, extinction rate is a constant function of the proportion of occupied patches.

  • Rescue effect, Immigration of individuals from nearby patches rescue populations from extinction.

Core Satellite Hypothesis

  • Bimodal distribution in patch occupancy.

  • Either very common or very rate in different metapopulations

Testing Metapopulation Theory

  • Ika Hanski study: Populations of Glanville fritillary butterfly in alpine meadows across Scandinavia.

Hanski's Findings

  • Number of occupied sites changes indicating extinction/colonization.

Testing Colonization

  • Probability of a local population increases with the size of neighboring populations, evidence against propagule rain.

Testing Extinction

  • Probability of extinction declines with neighboring populations, evidence for rescue effect.

Core Satellite Hypothesis

  • Metapopulation divided into semi-independent patch networks.

  • Showed bimodal distribution of abundance

Incidence Function

Simplifying Assumptions of Levens Model

  • Spatially implicit. Doesn't account for spatial location, only constant dispersal likeihood.

Patch Area

  • Smaller habitat has less resources and support smaller populations.

Patch Isolation

  • Patches far apart have smaller chance of being colonized.

Patch Synchrony

  • High correlations in environmental fluctuations increases risk of regional extinction.

Alternative Models

Hansen's Incidence Function Approach

  • Easy data collection, but assumes equilibrium when data is collected

State Transition Models

  • Uses transition models for each patch at certain time points.

Demographic Methods

  • Considers demo data e.g. dispersal, reproductivity, etc.

Equation Summary

  • Models based on CI(rate of colonization per year in patch) and EI(extinction rate per year for patch I)

Model Fitting

  • Involves statistically fitting CI and EI to parameters that have relevant biological meaning.

  • Tested and accurate based on Hansen data.

Conservation Decisions

  • Incident function models based on patch sizes of populations help determine conservation and restoration techniques.