Landscape Ecology

Metapopulations

Landscapes experience both natural and (increasingly) anthropogenic fragmentation, which has important ramifications on the structure and persistence of populations of organisms. Metapopulations are literally populations of populations, such as spatially subdivided populations existing in discrete habitat remnant patches as a result of habitat fragmentation. The metapopulation concept has changed how ecologists view spatial heterogeneity and judge the impacts of fragmentation, effecting a paradigm shift from a static patch-matrix island biogeography perspective to a more dynamic view. From a highly theoretical beginning, the metapopulation concept has become increasingly used in conservation, epidemiological, and genetic applications. Knowledge about the properties of metapopulations may assist in predicting and preventing extinction events, designing reserves, measuring the spread of disease, and characterizing other topics of interest.

Why should we care about metapopulations?

  • There are many examples of how including spatial patchiness generates ecological effects that would not be present in the absence of a spatially heterogeneous system:

-competition (where one species is clearly a loser in competitive interactions, patchiness allows coexistence); and

-predator-prey systems (in cases where a predator is locally efficient, patchiness may provide refugia for prey and thus enhance potential for future pest outbreaks).

  • Population genetics is increasingly concerned about the role of patchiness in mediating gene flow.
  • Conservation biology as targeted on rare species is especially concerned with habitat fragmentation and isolated populations.
  • Landscape ecologists claim spatial pattern as their own domain, so metapopulation biology is a key topic in landscape ecology. In this class, our interest in metapopulations is from the perspective of identifying those cases where the pattern of available habitat patches in a landscape has implications for population dynamics or persistence. These cases are of increasing concern in taking a landscape approach to conservation biology, especially with respect to the effects of the fragmentation of intact habitats into small and perhaps disconnected habitat remnants.

Terminology/definitions

Metapopulation –

Sensu stricto –

Sensu lato–

Subpopulation

a habitat patch

local extinction

recolonization

population turnover

winking dynamics

Click here for a list of terms and types of metapopulations.

History of the metapopulation concept

RichardLevins (1969) is the originator of the metapopulation concept and coined the term "metapopulation." He developed a model that keeps track of p, the proportion of patches occupied by a species of interest:

dp/dt = cp(1-p) - ep
where e and c are extinction and colonization rates, dp/dt is rate of change in ppn of patches occupied, cp(1-p) represents colonization of unoccupied patches ("birth" of new occupied patches), and ep represents local extinction ("death" of occupied patches)
predicted equilibrium: in the long run, the ppn of occupied patches will be:

pequil = 1 - (e/c)
Metapop. will only persist if c > e

This was the first model of population dynamics in a heterogeneous environment.

Previously, all other models considered populations to occur panmictically in a homogeneous system (a clearly unrealistic scenario).

Assumptions:

-patches are discrete

-patches are equal in quality

-all patches are equally accessible

-patches are structurally internally homogeneous

-patches are not delimited spatially explicitly

-local, within-patch population dynamics are independent of one another (not synchronous)

-unoccupied patches are not unsuitable nor become unsuitable over time (no succession)

-scale ignored

Then there was a 20+ year gap in metapopulation thinking. Why?

Types of metapopulations:

Susan Harrison has described several variations on the metapopulation theme (Harrison 1991, 1994; Harrison and Taylor 1997):

  • The "Classic" (Levins) Metapopulation (metapopulation sensu stricto)

Hanski and Gilpin (1991) further delineate some additional key characteristics of classic metapopulations:

At the local scale, individuals interact with each other during the normal course of feeding and breeding (living); an individual belongs to one local population for most of its life.

A metapopulation is a constellation of local populations that are linked by dispersal.

Not all spatially subdivided populations are metapopulations.

  • Mainland/Island Metapopulations
  • Source/Sink Metapopulations
    sources, sinks, and pseudosinks

density as a misleading indicator of habitat quality (see the classic paper by Van Horne 1983)
Sinks aren’t useless - may be important as stepping stones, providing greater connectivity in the metapop. as a whole (Foppen et al. 2000).

  • Patchy Populations
  • Non-equilibrium Metapopulations

Important note: a population may exist as different types of metapopulations at different times.

Population processes affecting metapopulations

Metapopulation dynamics reflect the occurrence and rates of local extinction and recolonization, and factors effecting these processes. Metapopulations subject to high extinction rates, but with correspondingly high rates of recolonization, also have high population turnover.

Factors affecting extinction

There are three proximate agents of local extinction that act in a stochastic manner (Shaffer 1981, Lande 1988):

Demographic stochasticity -

Genetic stochasticity-

Environmental stochasticity -

A fourth cause of local extinctions isdirectional habitat loss. In contrast to the stochastic agents above, these threats are more deterministic in their action. Many argue that these are the major controls on real metapopulations -

Factors affecting recolonization

Because recolonization depends on the successful establishment of new recruits in a habitat patch, the factors influencing recolonization must reflect the life-history traits that effect this.

For plants:
seed size and viability (often related to seed size);
dispersal vector (wind, water, animal);
habitat (seedbed) requirements.

For animals:
distance;
"resistance" of intervening habitats;
dispersal behavior (preference or avoidance of some habitats, search and orientation during dispersal, use of stepping stones or corridors);
mortality rates during dispersal itself, and agents of this mortality.

For both:
competition with individuals (or species) already out there.

Empirical studies of metapopulations

Metapopulations are logistically difficult to study. A metapopulation is defined by dispersal events that need occur only once every generation or so, and so it stands to reason that these events are unlikely to be witnessed in the field. This places an emphasis on modeling endeavors, yet empirical documentation is critical for applied endeavors.

Empirical studies of metapopulations have proceeded in a variety of ways (Kareiva 1990):

Most have dealt with short-lived species, often insects, for which short generations times make it a bit easier to observe metapopulation dynamics directly.

For larger and longer-lived organisms, metapop. dynamics are inferred indirectly from data like:

-Genetic similarity: in a metapopulation, we might expect to see spatial patterns in genetic similarity of individuals collected in different patches. This requires that the rates of genetic differentiation be appreciable relative to isolation time and also requires species with "well-behaved" genes. Giles and Goudet (1997) provide an in-depth case study and review other examples of applications of metapopulation theory to population genetics.

-Percent occupancy, or turnover in occupancy, in habitat patches as a function of between-patch distance or some other index of isolation. For example, one might use logistic regression to model patch occupancy (presence/absence) as a function of distance to the nearest other occupied patch.

-Similarity in demographic rates, or autocorrelation in population levels. For example, Smith and Gilpin (1997) found spatial autocorrelation in census-based population growth rates of the American pika, suggesting an important role of dispersal in influencing metapopulation dynamics.

Because of these difficulties, Harrison (1991, 1994; Harrison and Taylor 1997) reviewed the empirical evidence in support of metapopulations and suggests that although there are a few cases that are sufficiently well-documented to support the existence of metapopulation dynamics, in more cases the evidence is simply not strong enough to demonstrate that metapopulation dynamics are occurring.

Examining metapopulations: one example

The logistical difficulties of examining metapopulations empirically led Keitt et al. (1997) to pursue an alternative approach that did not require detailed information about the dispersal behavior of the species of interest (in this case, the Mexican Spotted Owl). They instead focused on the pattern of habitat patches, and asked the question, "What can we infer about this (meta?)population, given the pattern of available habitat and limited knowledge of the biology of the species?" They began with a postulated map of potential habitat for the owl (based on known ecological requirements of the species), and developed an analysis to quantify habitat pattern relative to the owl's estimated dispersal capabilities. The analysis consisted of a few simple steps:

1. Define a raster map of clusters of potential owl habitat (in this case, derived from remote-sensing images).

2. Aggregate the cells of the map into discrete clusters based on functional adjacency at a specified joining distance (dispersal distance). In this, two cells were in the same cluster (habitat patch) if they were within the specified joining distance. The presumption was, if owls could disperse that distance, the cells would function for an owl as part of the same habitat patch.

3. This clustering aggregation was repeated for a wide range of joining distances/potential dispersal distances (0, 5, 10, ..., 100 km).

4. Habitat connectedness was summarized as length of habitat, indexing how "connected" the habitat patches were at a given joining (dispersal) distance.

The question is, given that the habitat patches coalesce at some joining distance to form essentially a single large patch, at what distance does this occur, relative to the dispersal capabilities of the species? A habitat mosaic that coalesces at joining distances that are well within the dispersal capabilities of the species would not be experienced as discrete habitat patches (the species might function as a single patchy population). A landscape that coalesced well beyond the dispersal range of the species would be experienced as a collection of discrete patches (the species would operate as some sort of metapopulation).
A habitat mosaic that coalesces at a joining distance similar to the dispersal range of the species would be expected to behave as a metapopulation.

The elegance of this approach is that it does not require exhaustive information about the dispersal range of the species (nor mortality, nor fitness)--it requires merely that we know its approximate dispersal range relative to the critical joining distance at which the landscape coalesces!

Keitt et al.’s paper is available free online (URL is given in the reference section below).

Epilogue

The metapopulation concept has changed how biologists think about the world: it has gotten them to think about patches and dispersal. In other words, it has gotten them to think like landscape ecologists.

References:

Foppen, R.P.B., J.P. Chardon, and W. Liefveld. 2000. Understanding the role of sink patches in source-sink metapopulations: Reed Warbler in an agricultural landscape. Conserv. Biol. 14:1881-1892.

Giles, B.E., and J. Goudet. 1997. A case study of genetic structure in a plant metapopulation. Pp. 429-454 in: Metapopulation Biology: Ecology, Genetics, and Evolution (I. Hanski and M. Gilpin, eds.). Academic Press, San Diego, CA.

Hanski, I., and M. Gilpin, eds. 1991. Metapopulation Dynamics: Empirical and Theoretical Investigations. Academic Press, London, UK.

Hanski, I., and M. Gilpin, eds. 1997. Metapopulation Biology: Ecology, Genetics, and Evolution. Academic Press, San Diego, CA.

Hanski, I., and O. Ovaskainen. 2003. Metapopulation theory for fragmented landscapes. Theoret. Pop. Biol. 64:119-127.

Harrison, S. 1991. Local extinction in a metapopulation context: an empirical evaluation. Biol. J. Linnean Soc. 42:73-88.

Harrison, S. 1994. Metapopulations and conservation. Pp. 111-128 in: Large-scale Ecology and Conservation Biology (P.J. Edwards, N.R. Webb, and R.M. May, eds.). Blackwell, Oxford, UK.

Harrison, S., and A.D. Taylor. 1997. Empirical evidence for metapopulation dynamics. Pp. 27- 42 in: Metapopulation Biology: Ecology, Genetics, and Evolution (I. Hanski and M. Gilpin, eds.). Academic Press, San Diego, CA.

Kareiva, P. 1990. Population dynamics in spatially complex environments: theory and data. Phil. Trans. R. Soc. Lond. B 330:175-190.

Keitt, T.H., D.L. Urban, and B.T. Milne. 1997. Detecting critical scales in fragmented landscapes. Conservation Ecol. 1(1):4.

Lande, R. 1988. Genetics and demography in biological conservation. Science 241:1455-1460.

Levins, R. 1969. Some demographic and genetic consequences of environmental heterogeneity for biological control. Bull. Entomol. Soc. Am. 15:237-240.

Pulliam, H.R. 1988. Sources, sinks, and population regulation. Am. Nat. 132:652-661.

Shaffer, M.L. 1981. Minimum populations sizes for species conservation. BioScience 31:131- 134.

Smith, A.T., and M.E. Gilpin. 1997. Spatially correlated dynamics in a pika metapopulation. Pp. 407-428 in: Metapopulation Biology: Ecology, Genetics, and Evolution (I. Hanski and M. Gilpin, eds.). Academic Press, San Diego, CA.

Van Horne, B. 1983. Density as a misleading indicator of habitat quality. J. Wildl. Manage. 47:893-901.

Watkinson, A.R., and W.J. Sutherland. 1995. Sources, sinks, and pseudo-sinks. J. Anim. Ecol. 64:126-130.