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Pearson Scott M. (2013) Landscape Ecology and Population Dynamics. In: Levin S.A. (ed.) Encyclopedia of Biodiversity, second edition, Volume 4, pp. 488-502. Waltham, MA: Academic Press.

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48

Landscape Ecology and Population DynamicsScott M Pearson, Mars Hill College, Mars Hill, NC, USA

Published by Elsevier Inc.

GlossaryCore and satellite model Network of habitat patches in

which centrally located core patches harbor

stable populations that provide emigrants (or colonists) to

ephemeral populations in peripheral satellite patches.

Deme Localized breeding group or subpopulation, often

confined to a single habitat patch.

Effective population size (Ne) Number of individuals in

population that participate in breeding.

Extinction vortex Complex of interacting mechanisms

that lead to the extinction of small populations.

These mechanisms include loss of genetic diversity

as well as environmental and demographic

stochasticity.

Habitat fragmentation Process in which habitat loss

converts a landscape dominated by large connected patches

Encyclopedia of Bi8

of habitat to one in which habitat exists in small,

disconnected patches or a condition in which

habitat is spatially distributed as small, disconnected

patches.

Landscape matrix The complex of habitats occupying the

space between habitat patches.

Metapopulation Network of individual demes connected

by the processes of immigration and emigration.

Population dynamics Change in population size through

time and the processes that bring about these changes.

Sink population Deme in which death rates exceed

birthrates. Sink populations will go extinct without an input

of immigrants.

Source population Deme in which birthrates exceed

death rates. Sources produce an excess of individuals that

emigrate from that deme.

Introduction

The discipline of landscape ecology emphasizes the causes and

consequences of spatial pattern on the functioning of popu-

lations, communities, and ecosystems. Nature is generally not

homogenous with respect to ecological properties. Those

properties include gradients in abiotic factors, such as the

temperature, moisture, and the abundance of required re-

sources; and biotic factors, such as the presence of predators,

pathogens, and competing species. This spatial heterogeneity

exists at multiple scales of space and time. The term ‘‘land-

scape’’ evokes patterns over a broad scale, such as the view

from an airplane or satellite extending over several square

kilometers and including the mosaic of forests, grasslands,

wetlands, agricultural fields, and urban areas seen below

(Figure 1). This mosaic and the diversity of habitats therein is

the setting where species make their living. The spatial pattern

of habitats determines how species and their populations are

distributed across this view from above. The influence of

spatial pattern is also important at finer scales. Studies in

landscape ecology have illustrated how the spatial pattern of

resources at the scale of 1 m2 altered the habitat use by beetles

and ants (Wiens and Milne, 1989; Wiens et al., 1993). ‘‘Scale’’

is an important concept in landscape ecology because the

influence of spatial patterns often depends on the scale in

which they are observed and measured. It is common to

measure spatial heterogeneity at multiple scales in order to

best discern which scales are important for a given ecological

phenomenon (e.g., Price et al., 2005). No matter what scale is

studied, the spatial pattern of resources alternatively provides

opportunities for population spread and increase, limits and

constrains population growth, or threatens the persistence of

some species.

Basic Concepts and Terminology about Population Dynamics

A population is a group of interbreeding organisms that pro-

duce viable, fertile offspring; under the biological species

concept, members of a population belong to a single species.

Localized breeding groups are also known as ‘‘demes.’’ In a

typical landscape, the suitable habitat for most species exists in

a patchy pattern (Figure 1), so patches of habitat usually de-

fine the location and boundaries of demes.

Ecologists are interested in the number of individuals in a

population (that is, population size classically denoted by the

letter N). The change in N through time (dN/dt) is population

dynamics. Population size changes by the demographic pro-

cesses of birth, immigration, death, and emigration (BIDE).

This BIDE model of population growth is

dN=dt ¼ Birthsþ Immigrants2Deaths2Emigrants:

Populations in which immigration and/or emigration oc-

curs are considered to be open populations and are connected

to other demes by the movement of individuals. The distances

between demes influence the frequency of these deme-to-

deme movements. Movements may happen regularly for the

population but occur infrequently during the life cycle of an

individual. Movements often take the form of dispersal from

the natal site to a different habitat patch. Dispersal lessens the

probability of competition and interbreeding with parents and

siblings, especially when the population in the natal patch is

small. Analyses of population viability and genetic diversity

emphasize effective population size (Ne), which is the number

of individuals actually participating in breeding. In most

populations, NeoN because some individuals are un-

successful in attracting a mate, reproductively immature, or of

postreproductive age.

odiversity, Volume 4 http://dx.doi.org/10.1016/B978-0-12-384719-5.00417-2

Aerial photograph

0 0.25 0.5 1 Km

Roads

Streams

Hardwood

Agriculture

Miscellaneousnonforest

Wetland

Conifer

Mixed forest Developed

Classified land cover

Figure 1 Landscapes are a mosaic of habitat types. Color infrared aerial photograph from 1998 (left) and classification of land cover in 2001(right) for a region of southern Appalachian Mountains, Madison County, NC, USA.

Landscape Ecology and Population Dynamics 489


Population Dynamics in LandscapesThe number of individuals in a population, N, is limited

by available resources. The limiting resource(s) may include

food or nest sites for animals, or moisture, sunlight, and/or

soil nutrients for plants. Suitable habitats are the locations

and conditions that provide these resources. Given that re-

sources are finite, N has a maximum value that is sustainable.

Ecologists use the term carrying capacity (K) to refer to

the maximum N that a given environment can support

over the long term. The logistic growth equation is a simple

model of population dynamics learned by most students of

ecology:

dN

dt¼ rN

K �N

K

� �

The value dN/dt represents change in N over a unit of time (t),

and r is the intrinsic rate of increase, which is a measure of per

capita population growth:

r ¼ births� deaths

N

Assumptions of this model include a closed population (i.e.,

there is no immigration or emigration) and that r and K are

constants. Other ecological forces that could influence popu-

lation growth, such as predation or competition, are not in-

cluded. The logistic growth model implies that a population

attains equilibrium with resources in its environment. The

continuous form of this model produces graphs of N against

time as an S-shaped curve in which the population grows until

N¼K and then N remains constant at that value. The as-

sumptions of the logistic growth model are rather restrictive,

and very few if any populations in nature would fulfill all of

them. Nevertheless, it expresses a central premise that popu-

lations are limited by availability of resources and the amount

of habitat in the landscapes where they live. Furthermore,

landscape ecologists study how the spatial arrangement of

habitat patches can alter population dynamics.

Landscape-level changes in habitat abundance and spatial

pattern affect population dynamics. Data on populations of

grassland birds in North America provide example of how

changes in habitat availability alter population size. At the

continental scale, the abundance of bird species that require

grassland habitats has been declining since the mid-1900s in

MAC_ALT_TEXT Figure 1

Population trends for two grassland birds

40

45

50

35

25

30

20

10

EA

ME

abu

ndan

ce in

dex

15

0

5

25

FIS

P a

bund

ance

inde

x

30

Field sparrow

Meadowlark

Regional response to habitat protection

20

10

15

0

5

200

250

150

50

100

Reg

iona

l abu

ndan

ce(B

irds/

5000

hou

rs)

019751965

(a) (b)

1985 1995

Year

2005 1975 1980 1985

Henslow’s sparrow

1995

Year

1990 2000 2005

Figure 2 Change in abundance for grassland birds at (a) continental scale for eastern North America and (b) regional scale for Illinois. (a) Datafor Eastern meadowlark (Sturnella magna) and field sparrow (Spizella pusilla) provided by United States Geological Survey (USGS) NorthAmerican Breeding Bird Survey, http://www.mbr-pwrc.usgs.gov/bbs/bbs.html. Solid line is mean estimate, with dashed lines showing 95%credible interval. (a) and (b) Reprinted from Herkert JR (2007) Evidence for a recent Henslow’s Sparrow population increase in Illinois. Journal ofWildlife Management 71: 1229–1233, with permission from Wiley.

490 Landscape Ecology and Population Dynamics


North America (Peterjohn and Sauer, 1999; Figure 2) and

parts of Europe (Chamberlain and Fuller, 2001; Figure 2).

These declines can be explained by the loss of grassland

habitats because of changing agricultural practices, expansion

of suburban development, conversion of grassland habitats to

forests, and long-term disruption of ecological processes (e.g.,

fire and grazing) that create and maintain grassland habitats

(Askins et al., 2007). Landscape-level analyses have revealed

the specific habitat features required for foraging and nesting

by these birds (Ribic and Sample, 2001; Veech, 2006). These

species are sensitive to the fragmentation of their habitats. In

response to these population declines, management initiatives

at the regional scale have focused on habitats protection and

restoration. One such initiative is the US Department of

Agriculture’s Conservation Reserve Program (CRP). The CRP

encourages the protection of large patches of grassland habitat

and has the potential to increase habitat availability for these

birds. Herkert (2007) documented an increase in Henslow’s

sparrow (Ammodramus henslowii), an obligate grassland spe-

cies, in response to the establishment of 400,000 ha of CRP

lands in Illinois (Figure 2) but cautioned that local manage-

ment practices (such as farmers’ mowing schedules) can affect

habitat quality. The positive effects of similar habitat restor-

ation efforts have been documented in other regions (e.g.,

Benson et al., 2006).

Monitoring population dynamics at the landscape scale is

challenging. Various survey techniques are available for esti-

mating population size, but measurement of demographic

rates is more difficult. It is generally necessary to estimate

demographic rates (i.e., births, deaths, and immigration) by

sampling a limited number of sites or habitat patches in the

landscape because of the large effort required to produce these

estimates. Often it is the variation in demographic rates

among habitat patches that is of greatest interest. For example,

Herkert et al. (2003) sampled 39 sites to estimate the effects of

patch size on nest survival and parasitism in three grassland

bird species. In a study of song sparrow (Melospiza melodia)

populations, Jewell and Arcese (2008) linked the population

growth rates of the sparrows indirectly to landscape-level

patterns of land use (Figure 3). Rates of brood parasitism by

cowbirds (Molothrus ater) reduced sparrow reproduction, and

cowbird abundance was strongly correlated with land uses

such as urban and agricultural lands with livestock grazing.

These land uses created areas where parasitism rates were so

high that local reproduction in sparrow populations could not

replace individuals lost to mortality (i.e., ro0). Their results

suggest that these populations were maintained by immi-

gration from areas with lower parasitism rates rather than by

local reproduction.

Simulation models are often employed to explore the ef-

fects of landscape patterns on population dynamics. Spatially

explicit models can simulate the occupancy of specific lo-

cations as well as the demographic rates characteristic of

populations at those locations. Such models allow the re-

searcher to test hypotheses about population dynamics in the

complex settings of real and theoretical landscapes. These

models are especially useful for studying the impacts of vari-

ous scenarios of landscape change on populations. Pearson

et al. (1999) examined how management options related to

forest clearing would affect habitats, and therefore the abun-

dances, of a suite of native species. Complex population

processes such as survival, reproduction, and movement of

individuals can be represented in spatially explicit models. For

example, Holdo et al. (2011) used a model to study the impact

of road construction that would interfere with migratory

movements of the Serengeti wildebeest (Connochaetes spp.;

Figure 4). Their simulations suggest that this barrier to

movement could reduce wildebeest population by one-third

because these animals would be less able to migrate to the

most productive foraging sites. Locations of the most pro-

ductive sites shift in location seasonally, and the road inter-

fered with the animals’ ability to track and migrate to those

sites. Moreover, the road was predicted to divide a single

wildebeest population into two separate subpopulations.


1600

1200

Wild

ebee

st (

1000

s)

800

400

00 20 40 60

Time (yr)

Total population (no road) Northern subpopulation (road)Southern subpopulation (road)

1° S

3° S

33° E

Lake Victoria

Musoma

Wildebeestdry season

Wildebeestwet season

Migration route

Nairobi

Kenya

Tanzania

Arusha

Proposed roadTotal population (road)

80 100

Figure 4 Potential impact of a proposed road on Serengeti wildebeest populations. (a) Results of spatially explicit simulation model onabundance of wildebeest (Connochaetes spp.) comparing the landscapes with (red line) and without (black line) proposed road. The road wouldseparate wildebeest into northern and southern populations shown by blue and green lines. Graph reprinted from Holdo RM, Fryxell JM, SinclairARE, Dobson A, and Holt RD (2011) Predicted impact of barriers to migration on the Serengeti wildebeest population. Public Library of ScienceOne 6: 1–7. Map provided by Stuart Pimm, with permission from PLOS.

Brood parasitism rates

(a) (b)

Population growth

(km)012 4 6 8

N N

(km)012 4 6 8

Parasitism rate0⋅0−0.2 Low0⋅2−0.4 Moderate0⋅4−0.8 High

Expected population growth rate

< 0⋅90 Strong sink0⋅90−1⋅00 Weak sink1⋅00−1⋅10 Weak sourceNo song sparrows

Figure 3 Maps of brood parasitism and population growth of song sparrows (Melospiza melodia) in the Southern Gulf Islands of BritishColumbia, Canada. Rates of parasitism by brown-headed cowbirds (Molothrus ater) (a) are affected by land use and results in variation inpopulation growth rates of their sparrow hosts (b). Growth rates are expressed in terms of finite rates of increase. Rates Z1 indicate stable orgrowing populations (sources), whereas rates o1 represent declining or sink populations. Reprinted from Jewell KJ and Arcese P (2008)Consequences of parasite invasion and land use on the spatial dynamics of host populations. Journal of Applied Ecology 45: 1180–1188, withpermission from Wiley.



Although the overall abundance of required resources is

of great importance for populations, the patchiness and spa-

tial arrangement of habitat types have the potential to com-

plicate population dynamics in landscapes. Demographic

rates, such as survival and reproduction, may be affected by

patch size and shape. Movements between patches can be

influenced by the distance between patches and other spatial

features. Therefore, an understanding of how population dy-

namics play out in space is important for research and

management.





Landscape Structure and Population Dynamics

Landscape ecologists are interested in spatial patterns.

For populations, the overall abundance of habitat and its

spatial distribution have a strong influence on the genetic

structure and population dynamics of species. The concepts

of patch, matrix, and corridor are useful for understanding

how populations are influenced by the spatial structure

of landscapes (Figure 5). For the time being, assume

that patches are recognizable as discrete areas of similar

habitat and that all habitat patches contain suitable habitat

with enough resources to sustain a population. (This as-

sumption of discrete, homogeneous patches will be relaxed

later.) The unsuitable habitats found between habitat patches

comprise the landscape matrix. Corridors are linear strips of

habitat that connect patches and facilitate the movements

among patches (Figure 5). The number, sizes, shapes, and

spatial arrangement of habitat patches, as well as the presence

of corridors, impose a spatial structure on the species that

occupies them.

Several terms contain the word ‘‘structure.’’ The spatial

distribution of habitat may be referred to as ‘‘patch structure’’

when applied to a specific habitat type or as ‘‘landscape

structure’’ when applied to the spatial pattern of all habitat

types in the landscape. The term ‘‘population structure’’ refers

to the spatial distribution of breeding groups (i.e., demes) and

the rates of exchange of individuals, via emigration and im-

migration, among these groups. Much of the problem of

analyzing population dynamics at the landscape level relates

to understanding the influence of landscape (or patch) struc-

ture on population structure.

Satellite patches

Habitat patches

Core p

Stepping stones

Figure 5 Schematic diagram of patch–matrix–corridor model. In this exampatches. Individuals from the population of the core patch disperse to the sextinct. Linear corridors or closely spaced habitat fragments (stepping ston

Patches, Matrix, and Corridors

The patch structure of a landscape influences the dynamics of

populations living therein because patch structure affects the

spatial distribution of individuals and their movements

(Saunders et al., 1991). Patch size is one of most important

qualities of landscape structure because it is directly related to

local population size. Larger patches have a greater abundance

of resources and will support a greater N over the long term

(i.e., the patch’s carrying capacity), whereas smaller patches

support fewer individuals. Immigration and emigration are

affected by the distance between patches and the intervening

landscape matrix. When patches are far from one another, the

chance of successful movement between them is reduced.

Dispersing animals can suffer mortality from hazards of pre-

dation, starvation, or accident while crossing the

unsuitable matrix. The dispersal mechanisms of plant seeds

may fail to deliver them to distant patches, and dispersing

animals may not find a suitable patch.

Corridors connect patches and facilitate interpatch move-

ments. Similarly, small habitat patches (i.e., habitat fragments)

scattered throughout the matrix can act as ‘‘stepping stones’’ to

promote movement between large patches. Interpatch dis-

tances between these fragments are small, and the habitat

fragments provide temporary refuge for the dispersing animal

before crossing the next gap. Likewise, these fragments may be

too small to support a plant population over the long term,

but temporary populations can produce seeds capable of

colonizing nearby patches. The effectiveness of corridors and

stepping stones for movement can be altered by characteristics

of the landscape matrix (Baum et al., 2004; Vergara, 2011).

Satellite patches

Landscape matrix

Corridors

atch

ple, a centrally located core patch is surrounded by smaller satelliteatellite patches, which support smaller populations that frequently goes) facilitate movement among patches.




Characteristics of the landscape matrix may facilitate or

hinder movement. Habitats in the matrix may be harsh or

benign relative to the resource needs of individual species. The

matrix may contain barriers to movement. The barriers in-

clude natural features such as rivers or mountains and human

constructed features such as roadways, agricultural fields, and

urban areas. The relative ease or difficulty of movement

through the landscape matrix is called its permeability. The

spaces between habitat patches, filled by the matrix, are called

gaps. A species’ ability to move across this space is called its

gap-crossing ability. Gap-crossing ability and matrix permea-

bility for a given species in a particular landscape depend on

the life-history characteristics, habitat needs, and vagility of

the species as well as the matrix itself (Chardon et al., 2003;

Baguette and Van Dyck, 2007). For example, a bird can readily

fly across 100-m wide plowed agricultural field, but that same

field is a barrier to a salamander, which risks predation or

death by desiccation during an attempt to cross it.

Landscape ContextThe suitability and uses of particular habitat patches may be

affected by landscape context. The matrix and landscape-level

abundance of similar habitats alter the abundance of a species

at the patch scale (Radford and Bennett, 2007). When a given

habitat type is abundant in the broader landscape, then it is

more likely to see occupancy or visits to small patches (Pear-

son, 1993; Lewis et al., 2011). This effect has been documented

in mobile animals, such as mammals, flying insects, and birds,

which readily move between patches. Landscape context af-

fects plant population dynamics by altering pollination ser-

vices and rates of seed predation (Steffan-Dewenter et al.,

2001). The abundance and diversity of habitats in the broader

matrix affect the probability that pollinators or seed predators

will visit a given patch. Some animal species depend on a

variety of habitat types during their lives and the ability to

move among them. These species may be especially sensitive

to landscape context. For example, some amphibians require

wetlands for breeding but then disperse to upland habitats

after the breeding season (Pillsbury and Miller, 2008). Such

species require different habitat types in different seasons or

different parts of their life cycles. Therefore, a mix of patch

types that provide supplementary or complementary resources

(sensu Dunning et al., 1992) must be considered when as-

sessing habitat quality and quantity at patch and landscape

scales. By altering rates of immigration and emigration,

landscape context can affect the genetic diversity and di-

vergence among populations (Blevins et al., 2011).

Quantifying Landscape Structure and ConnectivitySpatial metrics provide a means of quantifying the spatial ar-

rangement of habitat. The most straightforward metrics focus

on the statistical distribution of patch sizes. First, the land-

scape is classified into suitable versus unsuitable habitat (i.e., a

binary landscape), and the areas of suitable patches are tallied.

Then the ‘‘number of patches,’’ ‘‘mean patch size,’’ and ‘‘size of

the largest patch’’ are useful for comparing landscapes with

similar amounts of habitat but having a different spatial ar-

rangement of habitat. Other metrics can measure more com-

plex aspects of spatial pattern such as the shape of patches.

These metrics incorporate a ratio of perimeter-to-area for

patches. Compact shapes, such as circular or square patches,

have a lower perimeter-to-area ratio, whereas elongated pat-

ches or those with complex shapes have a greater perimeter-to-

area ratio. The metric of ‘‘contagion’’ (e.g., Riitters et al., 1996)

measures the intermixing of habitat types, which is correlated

with number of patches as well as patch size and shape. There

are many spatial metrics available, and many are correlated

with each other (Hargis et al., 1998). No single metric will

measure all of the important aspects of spatial pattern. The

best choices will be those metrics that measure the qualities of

landscape structure predicted to influence the population

processes under study. One of the most important qualities is

habitat connectivity, which measures the ease of moving be-

tween habitat patches.

Landscape ecologists have developed a variety of metrics

for measuring the connectivity of landscapes (Kindlmann and

Burel, 2008). These metrics incorporate the interpatch dis-

tances, area of habitat at various distances from the focal

habitat, and the presence of stepping stones and corridors

(Leidner and Haddad, 2011). A proximity index rates the

relative amount and distance to suitable habitat for single

patches (Gustafson and Parker, 1994). Deciding which among

the available metrics is the best choice for any given species

remains challenging. Furthermore, connectivity has been

treated as both independent and dependent variables in

landscape ecology research (Goodwin, 2003). When con-

sidered an independent variable, connectivity was considered

a structural aspect of the landscape under study. These studies

often compared the performance of populations living in

landscapes having different patch structures. When treated as a

dependent variable, connectivity was a function of various

species responses to pattern in the same landscape. A highly

mobile species, such as a bird or large mammal, can easily

move between patches, but a sedentary organism or nonflying

invertebrate will find the same landscape disconnected (or

fragmented) if it cannot readily move among patches. Thus,

sensitivity to habitat loss and fragmentation depends on spe-

cies’ habitat needs and life-history traits (Driscoll and Weir,

2005; Sutton and Morgan, 2009).

Landscape Structure, Population Viability, andConservation

Conservation biology naturally considers the effects of

landscape structure on population structure and population

viability. Therefore, there is a close and complementary con-

nection between the disciplines of Conservation Biology and

Landscape Ecology. The conservation of any species depends

on the maintenance of viable populations, and the patch

structure of landscapes affects population viability at both the

patch and landscape level.

Population Viability in Small Patches

Population viability is strongly related to effective population

size (Ne) and genetic diversity, two characteristics that are

linked. Small populations suffer from demographic stochas-

ticity and reduced genetic diversity. Populations in landscapes



in which small isolated patches predominate show less genetic

diversity overall than populations in unfragmented landscapes

(e.g., butterfly (Collier et al., 2010) and toad (Allentoft et al.,

2009)). Moreover, population sizes in small patches fluctuate

to a greater degree because of demographic stochasticity,

which is the fluctuation in Ne, birthrates, and death rates

through time. They also fluctuate as a result of environmental

stochasticity, which is variation in demographic rates from

unpredictable events related to factors such as weather. Such

fluctuations create a greater chance of extinction and expose

the population to loss of diversity because of genetic drift and

population bottlenecks.

The viability of populations in small patches is reduced

because of limited genetic diversity. Small populations contain

less genetic diversity because there are fewer individuals. In

addition, genetic drift and inbreeding further reduce genetic

diversity over time. Genetic drift is the random change in allele

frequencies because of sampling error in the process of mat-

ing. Over the long term, drift ultimately leads to the loss of

alleles when their frequencies randomly reach zero. Levels of

heterozygosity, a common way of measuring genetic diversity,

are positively associated with population growth and persist-

ence (Hanski and Saccheri, 2006). Individuals with higher

levels of heterozygosity typically have higher survival and re-

productive rates than individuals with less heterozygosity

(Coltman et al., 1998). This phenomenon is called hetero-

zygote advantage or heterosis. Heterozygosity declines as al-

leles are lost and the population becomes fixed for one allele.

Similarly, inbreeding reduces heterozygosity among offspring

when related individuals breed, and inbred populations have

a greater chance of extinction (Saccheri et al., 1998). Inbred

offspring have lower levels of heterozygosity and have a

greater chance of being homozygous for deleterious recessive

alleles. This reduced fitness is termed ‘‘inbreeding depression.’’

In small populations, the choice of mates is directly related to

Ne, and matings among related individuals will inevitably

occur. The primary conclusion is that small populations have

lower genetic diversity and stochastic processes of genetic drift,

inbreeding, and population bottlenecks will further reduce

genetic diversity over time.

The predominance of small patches in fragmented land-

scapes can affect demography and behaviors. Small popu-

lations may suffer reduced population growth rates because of

social factors called Allee effects. Allee (1931) suggested that

some species have a minimum viable population (MVP) size.

Birth and death rates are density-dependent, and recruitment

drops to unsustainable levels below a certain N. For example,

fertilization rates in flowering plant may depend on visitation

rates by pollinating insects, but a minimum density of indi-

vidual plants is needed to attract the necessary numbers of

pollinators (Hackney and McGraw, 2001). When Ne or dens-

ities are too low, recruitment rates decline because of low

fertilization rates. Likewise, vulnerability to predators can in-

crease in some animal groups. Flock size and herd size are

correlated with the ability to detect predators and thereby re-

duce predation risk for the individual (Lima and Dill, 1990).

Allee effects are apparent when survival and reproductive rates

are positively correlated with population density and density

is below the threshold for density-dependent population

regulation (i.e., the carrying capacity). However, care should

be taken not to confuse these effects with the negative effects

of small population size such as inbreeding (Stephens et al.,

1999). In fragmented landscapes, the small patches may

support too few individuals needed to accrue the positive

benefits of population size and/or density. For animals, pat-

terns of behaviors such as movements can be altered by

habitat fragmentation. For example, Mitrovich et al. (2009)

found differences in the home range overlap and movements

and crowding for the coachwhip (Masticophis flagellum), a

large snake, in small patches relative to large patches. Move-

ments of large highly mobile mammals may be affected. too.

Seasonal movement behaviors of white-tail deer (Odocoileus

virginianus) varied with the mean size and number of patches

in a landscape in the midwestern USA (Grovenburg et al.,

2011). Deer in landscapes with many large patches tended to

be sedentary residents, whereas those in landscapes with small

patches were more likely to be migratory.

The genetic and demographic problems of small popu-

lations interact synergistically in a phenomenon referred to as

an extinction vortex (Gilpin and Soule, 1986). When Ne falls,

genetic diversity is lost because of the phenomena of bottle-

necks, drift, and inbreeding. Reduced genetic diversity causes

drops in population growth, reducing mean fitness because

genetic diversity is correlated with the levels heterozygosity in

individuals and the population as a whole. In small popu-

lations that have lost a significant amount of genetic diversity,

low or negative growth rates further reduce N, which results in

greater loss of genetic diversity. Moreover, reduced genetic

diversity limits the ability of the population to adapt, via

natural selection, to changes in its environment. Therefore,

small populations are more sensitive to environmental change

than large populations having more diversity. This combin-

ation of interacting processes eventually threatens the small

population with extinction.

What population size qualifies a small population?

Although the most accurate answer will depend on the life

history of specific species, the ‘‘50/500’’ rule of thumb from

conservation biology (Franklin, 1980) provides a useful starting

point when detailed life-history information is lacking. This

rule states that isolated demes with an effective population size

(Ne) greater than 500 will be relatively safe from the dangers of

the loss of genetic diversity. These risks progressively increase as

Ne declines from 500 toward 50. At Ne o 50, all combined

forces of the extinction vortex act on the population, and ex-

tinction may be inevitable without management intervention.

Thus, a Ne450 is needed for short-term population viability

and Ne4500 needed for long-term viability. The ‘‘50/500’’ rule

was based on goal of maintaining genetic diversity (Franklin,

1980). Shaffer (1981) outlined the concept known as the

minimum viable population. Estimates of a MVP include three

parameters: a Ne, a probability of extinction (or persistence),

and a specific time period. For example, ‘‘An MVP for any given

species in any given habitat is the smallest isolated population

having a 99% chance of remaining extant for 1000 years

despite the foreseeable effects of demographic, environmental,

and genetic stochasticity, and natural catastrophes’’ (Shaffer

1981, p. 132). When incorporating the dangers of demographic

and environmental stochasticity, the minimum Ne should be

in the range of thousands rather than hundreds (Traill et al.,

2010).



Some scientists criticize the notion of general guidelines for

MVPs, arguing that the minimum Ne for long-term persistence

must be determined on a species-by-species basis (Flather

et al., 2011). Population viability and MVP will be affected by

the unique combination of species’ traits, including its phyl-

ogeny, life history, resource needs, habitat availability, popu-

lation structure and demography, and environmental threats

(both natural and human caused) within the context of the

landscape where it lives. For landscape-level conservation ef-

forts, it should be more profitable to identify and address the

specific causes of population declines (Caughley, 1994) rather

than focus on maintaining a minimum number of indi-

viduals. Nevertheless, an estimate of MVP can be useful for

labeling species as being at risk of extinction, motivating

policy makers and managers to take appropriate actions, and

setting a target population size for restoration efforts.

Immigration and Rescue Effects

Despite the problems described in the previous section, small

populations are frequently observed in nature and seem to

persist over the long term. Their persistence can be explained

by the fact that these populations are open and connected to

other demes in the landscape via the movement of indi-

viduals. Population biologists commonly refer to these

movements as ‘‘immigration’’ (into) and ‘‘emigration’’ (from)

when in reference to a specific deme.

Immigration has several benefits to a small population and

some risks. Immigrant individuals can increase genetic diver-

sity if they bring alleles that are absent or rare in the deme.

Even infrequent or low levels of immigration are sufficient to

restore genetic diversity lost to genetic drift (Slatkin, 1985).

Immigrants provide a form of gene flow. The interpatch

transport of gametes, such as pollen for flowering plants, is

another example of gene flow. Moreover, immigrants provide

a form of population growth when local recruitment rates are

low (see BIDE model in the section Basic Concepts and Ter-

minology about Population Dynamics). Thus, immigration

can periodically rescue a population from the negative effects

of demographic stochasticity and loss of genetic diversity, but

there are significant risks associated with the movement of

individuals. ‘‘Outbreeding depression’’ occurs when immi-

grants introduce genetic traits that are poorly suited for the

local environmental conditions. Offspring expressing these

traits will have reduced fitness, and the mean fitness of the

population will be lower until natural selection eliminates

these traits. If immigration of these traits persists, then the

mean fitness and population growth rate will be determined

by a balance between immigration and selection. A second

risk is the introduction of pathogens and parasites carried by

immigrants.

Preserving Habitat at Landscape Level: The SLOSS Debate

Conservation biologists have debated the best strategy for

preserving habitat for threatened and endangered species. If

the total area of habitat that can be protected is limited, then

what is the best scheme for distributing that habitat in space?

The essence of this question is whether to protect the same

acreage of habitat in ‘‘single large or several small’’ (i.e., the

acronym SLOSS) patches. There are advantages and dis-

advantages for both choices (Diamond et al., 1976). A single

large preserve provides habitat to support the largest possible

population. If Ne is sufficiently large, then this choice will

avoid the problems of small populations discussed previously.

However, the danger of a single habitat patch is that some

environmental catastrophe such as a hurricane or fire or an

introduced virulent pathogen could extirpate the entire spe-

cies. If the species is spread across several smaller patches

sufficiently separated in space, then the chance of a cata-

strophic event affecting all of them is less than if they are

confined to a single patch. For the ‘‘several small’’ strategy to

be viable, the demes of respective patches must be large

enough to avoid the extinction vortex, or the populations

must be open to movement between patches in order to ac-

crue the benefits of immigration. The movement of immi-

grants may be natural or facilitated by human management in

the form of translocations of individuals.

Land management around preserved patches may include

the preservation of corridors to connect patches and facilitate

movements among them. Corridors likewise have their rela-

tive advantages and disadvantages (Haddad et al., 2011), and

their effectiveness depends on the natural history of the target

species (Gilbert-Norton et al., 2010). Species that are dispersal-

limited or have difficulty crossing the landscape matrix receive

the greatest benefits corridors. For animals, corridors of low-

quality habitat can enhance movement among habitat patches

even if populations cannot persist within the corridor itself

(Haddad and Tewksbury, 2005).

Landscape Ecology and Metapopulation Dynamics

Most populations in nature have a patchy distribution because

of patchiness of their habitat, and population structure is

determined by the exchange of individuals (e.g., immigration

and emigration) among patches. If the rates of exchange are

high and frequent, such as by a highly mobile species, then

there is simply one population occupying multiple patches. If

exchanges among patches are very infrequent or nonexistent,

then each patch has a distinct and separate population. An

intermediate level of exchange would include regular move-

ments among patches by dispersing individuals moving from

their natal site to another patch. This amount of exchange

characterizes metapopulations.

The dynamics of open populations persisting in a patchy

landscape often take the form of a metapopulation. A meta-

population is a network of individual demes connected by the

processes of immigration and emigration. Metapopulation

dynamics exist when species have demes in discrete habitat

patches. Each deme has a finite probability of extinction,

but extinction events are not synchronized in time across

space. Empty patches are common, but none of them are

too isolated to be recolonized from an extant deme. Thus,

a metapopulation exhibits turnover in the occupancy of

patches that is a function of local extinctions and recolon-

izations (Hanski, 1999). McCullough (1996) provides

examples of metapopulation ecology applied to problems of

wildlife conservation.



Metapopulation theory has been an important tool for

helping ecologists think about population dynamics in frag-

mented landscapes, but detecting metapopulations and para-

meterizing metapopulation models from field data is still

challenging (Driscoll, 2007). The incidence function model of

(Hanski et al., 1996b) has been one of the most useful because

it requires only patch occupancy data. By monitoring how

many and which patches are occupied over time, ecologists

can relate the probability of occupancy to patch size, shape,

and isolation. Alternative techniques include analyses of

genetic structure to infer the relative isolation of habitat pat-

ches and the frequency of immigration among them (Wang

et al., 2008).

Sources and Sinks

In the simplest case of population structure, the size of patches

and the quality of habitat contained within them is similar,

but this case is likely uncommon in nature. In a metapopu-

lation spread over several habitat patches, variation in popu-

lation growth rates can exist because of patch-specific

differences in habitat quality, interspecific interactions, or

other ecological factors. Pulliam (1988) described the situ-

ation in which some patches have intrinsic rates of increase

(r¼birthrate�death rate) greater than 0 – that is, local

birthrates exceed local death rates. These patches were termed

‘‘sources’’ because local population growth will produce an

excess of individuals. The local population growth exceeds the

patch’s carrying capacity, and these excess individuals must

emigrate; if not, then feedbacks from local resource limitation

will reduce growth rates. In the same metapopulation, other

patches called sinks have ro0 because the local birthrate is

less than the death rate. If isolated from other populations,

extinction is inevitable for sink populations. However, sinks

can persist in the context of a metapopulation because excess

individuals from source patches can immigrate into sinks.

These sinks receive a demographic subsidy and are able to

persist because the sum of (birthsþ immigrants�deaths)Z0.

The knowledge of source and sink patches is critical for

understanding how a particular metapopulation functions.

This understanding is important for landscape-level conser-

vation efforts in which choices are made about the protection

(or allowing the destruction) of some fraction of the existing

patches. If a critical number of the sources patches are lost,

then the entire metapopulation will collapse (Hanski and

Ovaskainen, 2002). Unfortunately, patch occupancy alone is

not a reliable indicator of the source/sink status of individual

patches. The hard work of estimating demographic rates must

be undertaken to fully understand this aspect of population

dynamics.

Core and Satellite Model

In conservation planning, the ‘‘core and satellite model’’ of

habitat protection has been used at the landscape level (Shen

et al., 2008; Snep and Ottburg, 2008). This model envisions

critical habitat distributed in patches varying in area and

quality. Core patches support the largest Ne and populations

that persist through time. Core populations may act as

demographic sources, and their greatest value to the broader

metapopulation is to produce emigrants destined for satellite

populations (Runge et al., 2006). Small patches located near

the periphery of the core patches support small satellite

populations that periodically go extinct. Satellite populations

depend on immigrants from the core patches to avoid ex-

tinction or for recolonization after local extinction. Satellite

populations may be demographic sinks or simply have a small

Ne that is vulnerable to the problems of small populations.

Landscape Change, Habitat Fragmentation, EdgeEffects, and Extinction Debt

Landscape changes, particularly those caused by human land

uses, can alter the abundance and connectivity of suitable habitat.

Habitat fragmentation results when habitat loss converts a

landscape dominated by large connected patches of habitat to

one in which habitat exists in small, disconnected fragments.

Fragmentation of native habitats is happening on a global scale

(Riiters et al., 2000). This phenomenon affects habitat quality as

well as its quantity and spatial distribution. Consequentially,

fragmentation affects the spatial structure of populations. The

effects of fragmentation can be conceptually separated into

the effects of (1) reduced patch size and (2) increased patch

isolation. The processes of habitat loss and fragmentation often

occur concurrently, but Fahrig (2003) argued that their effects

need to be considered independently to best understand

the consequences of landscape change on populations and

communities.

In fragmented landscapes, the effects of small patch size are

confounded with edge effects. Small fragments have more

edge, which can alter habitat quality. Small habitat patches

have a greater edge-to-interior ratio because of simple geom-

etry. As the area of a circle (p� radius2) decreases, the per-

imeter of a circle (2� p radius) decreases more slowly. Circles

and squares are simple, compact shapes in which length and

width are approximately equal. Habitat fragments of elong-

ated and complex shapes have a greater amount of perimeter

compared to the area. The patch perimeter or ‘‘edge’’ is the

boundary between the habitat of the patch and the landscape

matrix, and the ecological conditions at the patch edge can be

modified by the conditions in the matrix (Matlack, 1993). For

example, consider a forest patch in a matrix of agricultural

fields. The edges of forest are drier, warmer, windier, and re-

ceive more sunlight than locations deep in the interior of the

forest patch. These altered conditions are termed ‘‘edge effects’’

and may extend some distance into the forest patch. Edge

effects also include differences in the biotic interactions. For

example, predation rates may be greater near edges. The ‘‘in-

terior habitat’’ – sites within the patch but some minimum

distance from the patch boundary – is considered free of edge

effects. Some species are sensitive to the differences between

edges and interiors. So-called ‘‘edge-sensitive’’ or ‘‘interior-

dependent’’ species avoid edges or experience lower survival

and/or reproductive rates in edges. As fragment size decreases,

the edge-to-interior ratio increases; edge-sensitive species have

less and less interior habitat for use. Below a particular patch

size, interior habitat is absent because edge effects penetrate to

all regions of the small patch. Therefore, interior-dependent



species are absent from the smallest patches that are domin-

ated by edge-tolerant species (Banks-Leite et al., 2010). Al-

though the example of forest habitat was discussed here, edge

effects also exist for grasslands and other nonforest habitats

(Renfrew et al., 2005).

The response of populations to the process of habitat loss

and fragmentation may lag behind the changes in habitat

quantity and quality. For example, some edge-sensitive species

may persist in habitat fragments in spite of the loss of interior

habitat. This lag occurs because individuals survive in small

patches but long-term recruitment rates drop below mortality

rates. Thus, small patches are occupied and some reproduction

may be occurring, but not enough for long-term population

persistence. In addition, the metapopulation dynamics may be

disrupted by the overall loss of participating patches or the

loss of a critical patch, and the metapopulation collapses

(Hanski et al., 1996a). Eventually, these species will go extinct

in this landscape, but extinction is delayed by the presence

of long-lived individuals and some low levels of reproduc-

tion. This delay is termed ‘‘extinction debt’’ (Hanski and

Ovaskainen, 2002; Honnay et al., 2005), and it depends on

the life history of species affected by habitat fragmentation

(Piqueray et al., 2011). Krauss et al. (2010) reviewed data for a

variety of species living in fragmented grasslands of Europe.

They found that long-lived perennial plant species were more

likely to exhibit extinction debt than short-lived, mobile spe-

cies such as butterflies. For species exhibiting extinction debt,

their distribution on the landscape is better explained by past

habitat patterns than by the distribution and quality of habitat

in the contemporary landscape.

Environmental Gradients and Habitat Heterogeneity atMultiple Scales

The concept of source and sink populations (Pulliam, 1988)

raised awareness of how variation in demographic perform-

ance among patches affects the occupancy of individual pat-

ches as well as the landscape-wide distribution of a

population. The spatial arrangement of patches is important

because sink patches may persist only if they are within the

dispersal window of at least one demographic source (Foppen

et al., 2000). In the original models of source and sink

metapopulations, within-patch conditions were considered

homogeneous, but this situation is seldom typical in real

landscapes. Spatial heterogeneity within patches may affect

demographic rates and population dynamics at fine scales.

For large patches, spatial heterogeneity in habitat quality

may create source–sink dynamics among sites within the

patch. Environmental heterogeneity can create a mosaic of

sites having higher and lower rates of survival, reproduction,

and recruitment (Meekins and McCarthy, 2001). Within-patch

heterogeneity can be especially high when patches are defined

by a coarse-level criterion, such as land-cover type, and fine-

scale heterogeneity is ignored. Fine-scale heterogeneity in

temperature, moisture, soil nutrients, etc. may be correlated

with occurrence of individuals (Palmer, 1990; Fraterrigo et al.,

2006) and demographic rates (Meekins and McCarthy, 2001).

If habitat quality is strongly correlated with fine-scale edaphic

conditions (or some other measure of resource abundance for

such food availability), then these conditions may be used to

estimate the demographic potential of a given site (Seydack

et al., 2000; Ecke et al., 2002; Gonzalez-Megias et al., 2005;

Flinn, 2007). Although not separated into discrete patches,

source-sink dynamics can occur among the sites within pat-

ches. The demographic rates associated with an entire patch

will be a function of the average habitat quality of its em-

bedded sites. Landscape ecologists, with their appreciation for

issues of scale, are well-equipped to study the relative effects of

within-patch, among-patch, and landscape heterogeneity on

population dynamics.

Changing patterns of biodiversity in changing landscapes

illustrate how spatial patterns at different scales interact with

population processes. In portions of Europe and North

America, forests are expanding following agricultural aban-

donment. New forest patches are developing from abandoned

farmland via the process of secondary succession; this new

habitat is also called postagricultural forest. The spatial ar-

rangement of old forest patches is of great importance for

native herbaceous plant species that depend on forest habitats.

At the landscape scale, the abundance and proximity of ‘‘an-

cient forests’’ (not cleared for agriculture) is correlated with

the patterns of plant diversity among recovering forest patches

(Matlack, 1994a, b). The ancient forests preserved a pool of

forest plant species during the time period of heavy agri-

cultural use in the landscape (Pearson et al., 1998). During the

period of recovery after the peak of agriculture, these species

are able to disperse from the ancient forests to the new forest

patches. Moreover, life-history traits influence the establish-

ment and persistence of populations (Vellend, 2003; Flinn and

Vellend, 2005) in particular patches. Verheyen et al. (2003)

studied the distribution of forest herbaceous plant species in

these postagricultural forests and their landscapes. They found

that recovery after disturbance is a two-stage process in which

the dispersal and colonizing ability of a species is initially

most important in establishing populations in new forest

patches. Next, after a species had colonized a new forest patch,

habitat quality and niche specialization of the species influ-

enced abundance and persistence within patches (also Pear-

son and Fraterrigo, 2011). The distribution of dispersal limited

plant species was not correlated with habitat quality at the

landscape scale because these species simply could not reach

isolated forest patches. In other words, habitat fragmentation

negated any effects of varying habitat quality for these post-

agricultural forests in the initial phase of recovery. Habitat

quality became important only if and when a species reached

a patch. This process takes many years to play out and will

affect forest biodiversity for a century or more of recovery

(Vellend et al., 2007).

Continuous Habitat Variability in Landscapes

The patch–matrix–corridor approach to characterizing spatial

pattern is useful for landscapes in which patches exist as dis-

crete readily identifiable units, and there are greater differences

among patches than within them. However, in many land-

scapes, habitat variation occurs along environmental gradients

that change relatively slowly across space (Figure 6). In such a

landscape, drawing a definite boundary to denote habitat

Streams

Contours

Wetter

Relative soil moisture

0 125 250 500 m

Drier

Figure 6 Map of predicted soil moisture as an example of continuous variation in habitat quality. Soil moisture is influenced by topographyshown by 10-m contour lines as well as slope, aspect, and surrounding landforms. Drier sites are found on ridges and peaks, whereas wettersites are located in ravines and valleys. This map was developed using a digital elevation model to calculate a topographic relative moisture index(Parker, 1982). (Reproduced with permission from Simon SA, Collins TK, Kauffman GL, McNab WH, and Ulrey CJ (2005) Ecological zones in theSouthern Appalachians: First Approximation. Asheville, NC: US Department of Agriculture, Southern Research Station. Forest Service ResearchPaper SRS-41). Map shows 50-m grid cells.



patches is nearly impossible because suitability varies in a

complex and continuous manner across space. In mountain-

ous landscapes, topography creates gradients in temperature,

moisture, and light related to elevation, aspect, slope, and

terrain shape (Figure 6). Instead of maps of discrete patches of

suitable and unsuitable habitat, these landscapes are best

represented by maps showing continuous variation in habitat

quality (Thompson et al., 2006; Franklin, 2009).

Quantifying the spatial pattern of habitats in these land-

scapes is challenging (Dorner et al., 2002). The statistical

characteristics of this continuous variation can be quantified

using a range of statistical techniques including blocking,

spectral analysis, measures of spatial autocorrelation (Turner

et al., 1991), or surface metrics (McGarigal et al., 2009). Pat-

terns of habitat heterogeneity can change between fine and

coarse scales, and these analyses can identify the particular

spatial scale(s) in which spatial pattern and population pro-

cesses are linked (Fortin and Dale, 2005). To be useful, the

analysis should be approached from an organism-based per-

spective; that is, landscape structure can be understood by

relating environmental gradients to the tolerances and re-

source needs of individual species (Cushman et al., 2010) and

to population processes such as dispersal ability and sizes of

home ranges. The influence of environmental gradients in

determining species distributions and community com-

position has long been recognized by the ecologists. However,

the theory and analytical techniques for studying populations

in these types of landscapes is still under development.

Landscape Structure and Interspecific Interactions

Interspecific interactions are important determinants of

population dynamics, and landscape structure can influence

these interactions. All species interact with predators, parasites,

competitors, and so on as the biotic portion of their en-

vironment. In breeding birds of forests, nest predation rates

are affected by both landscape-level and within-patch habitat

patterns (Lloyd et al., 2005). Predation rates increase as patch

sizes decline and the landscape-wide abundance of nonforest


Schematic

Time since disturbance (years)

0 10

(a)

(b)

20 40 ≥60

Stand origin0 1 2 4 km

Prior 1880 1900−1910 1936−1950 1986−2005

No data1951−19851911−19351880−1899

Forest stands

Figure 7 Illustration of a landscape as a shifting mosaic of sites in different stages of recovery from disturbance. In the schematic (a), sitesfully recover from disturbance after 60 years of recovery. A landscape in the Pisgah National Forest in North Carolina (b) is a mosaic of foreststands of various ages as measured by time since the year of stand origin. This pattern is a consequence of natural disturbances and humanland uses such as timber management.



habitats increases. Moreover, landscape structure influences

the movement patterns of different predator species so that the

risk of encountering a specific predator species depends on the

precise location in the landscape (Bergin et al., 2000). Con-

versely, spatial complexity can promote coexistence between

predators and prey. ‘‘Refugia’’ are habitats (or microhabitats)

where preys are relatively safe from predators. When predators

are abundant, refugia prevent them from driving their prey to

extinction.

Spatial heterogeneity is one of the principal explanations

for the coexistence of competing species (Amarasekare, 2003)

in community ecology. Coexistence can be achieved by niche

partitioning when species specialize on different habitats or

resources. Habitat heterogeneity within and among patches

promotes coexistence. Spatial structure and heterogeneity

through time are also necessary for the coexistence by the

competition–colonization trade-off (Tilman, 1994). In this

mechanism, competing species differ in their competitive

abilities and ability to colonize new habitat patches. The su-

perior competitors have low colonizing abilities, and the

better colonizers are poor competitors. Disturbance periodic-

ally kills off local populations of the superior competitor, and

for a brief time those sites or patches are empty. The superior

colonizer (but poor competitor) quickly occupies the empty

sites and holds them until the superior competitor arrives.

Regular, localized disturbances permit coexistence by con-

tinually providing habitat for the poor competitor (e.g.,

Debout et al., 2009). Coexistence is possible when the land-

scape is a shifting mosaic of disturbed patches and sites at

different stages of recovery from prior disturbances (Figure 7).

Disturbance and its effects on landscape structure through

time are a recurring research theme in landscape ecology.

Summary

Landscape ecology is concerned with the causes and con-

sequences of spatial pattern in nature at multiple spatial

scales. Spatial pattern in habitats and resources influences the

growth, persistence, and decline of populations. The

patch–matrix–corridor model of describing spatial hetero-

geneity is a useful conceptual model that is directly applicable

to populations. Species frequently exhibit a patchy distri-

bution in landscapes as a function of the spatial arrangement

of their habitats. This landscape-level pattern (i.e., the land-

scape structure) determines how populations are organized in




local breeding groups and how frequently individuals move

between these groups. This population structure in turn affects

population dynamics. Landscape structure, in combination

with life-history traits of a species, determines whether that

species exists as a single large population, as a metapopulation

of demes connected by movement of individuals, or as a

collection of separate isolated populations. An understanding

of population structure reveals the conservation challenges

facing many species. In landscapes in which habitat is highly

fragmented, isolated populations in small patches face a

number of problems ranging from loss of genetic diversity to

edge effects. Thus, the landscape ecology of populations is

related to conservation. Some landscapes exhibit continuous

variation in habitat quality, and the patch–matrix–corridor

model is not directly applicable. Techniques for describing

habitat heterogeneity at multiple scales are available, but

understanding how this type of variation affects population

dynamics is more challenging.

See also: Habitat Loss and Fragmentation. Metapopulations

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