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Dispersal, habitat fragmentation
and population viability
Jean-François Le Galliard
CNRS, Université Pierre et Marie Curie & ENS, France
Definitions and facts
Habitat fragmentation describes a state (or a process) of discontinuities
(fragments) within the preferred living area (habitat) of a species.
The classical paradigm of population ecology is that of a single, large and
homogeneous population, but it is widely recognised that most populations are
fragmented and heterogeneous
→ implications for ecological processes ?
→ effects on population viability and extinction dynamics ?
Habitat destruction vs. habitat fragmentation
Habitat destruction is associated with massive habitat
loss, fragmentation and habitat degradation
~ 83 % land surface affected by human activities
Forest fragmentation (green area)
in Finland from 1752 to 1990
Habitat destruction includes several processes:
• Reduction in the total area of the habitat
• Increase in number of habitat patches
• Decrease in habitat patches area
• Increase in isolation of habitat fragments
• Possibly, a decrease in habitat quality
Fahrig. Ann. Rev. Ecol. Syst. 2003.
Dispersal behaviour
Dispersal is the process of “going or distributing in different directions or over a
wide area” (Oxford English Dictionary)
Dispersal is a behaviour involving key steps
emigration
transfer and habitat choice
immigration / settlement
Dispersal can occur at any time during the life cycle
natal dispersal
breeding dispersal
Dispersal can also occur at many different spatial scales
Effects of habitat destruction on biodiversity
Habitat destruction is considered as one of the main cause of species loss on earth with
overexploitation and species invasion according to the 2006 IUCN statistics
• 16,119 species are threatened with extinction in the Red List.
• 99% of threatened species are at risk from human activities: humans are the main cause of
extinction and the principle threat to species at risk of extinction.
• Habitat loss and degradation are the leading threats: they affect 86% of all threatened
birds, 86% of the threatened mammals assessed and 88% of the threatened amphibians.
Examples of species threatened by habitat loss in Europe (21 listed endangered)
Erismature à tête blanche
Grenouille des Pyrénées
Silene diclinis
Demographic consequences of habitat
fragmentation
Ecology of fragmented habitats
Spatial structure : existence of discrete, localised patches of preferred
habitat separated by a matrix of non-preferred habitat
patchy distribution
spatial organisation : number and spatial distribution of patches
Local demography : small patches are more likely to go extinct and more
variable than large populations
Connectivity : patches are separated by a matrix of non-preferred habitat
putting limits on dispersal abilities
connectivity : number, size and spatial distribution of corridors
permeability : matrix quality and spatial structure
A case example: spatial population dynamics
Habitat fragmentation
Granville fritillary butterfly (Finland)
Hanski. Nature. 1998.
The Levin’s model of habitat fragmentation
Levin’s occupancy model
m×p
occupied
e
empty
p’ = m p (1 – p) – e p
p* = 0
p* = (m-e)/m
Very fast local dynamics
The population is in a balance between migration and extinction
There is a threshold migration rate for population viability (m = e)
below the threshold, the population is viable
above the threshold, the population goes extinct
Levins. Bull. Ent. Soc. Entom. USA. 1969.
A mesoscale approach of metapopulation dynamics
Disp. pool
0
1
2
3
…
K
Infinite number of discrete patches of size [0,K] individuals (demographic stochasticity)
Local stochastic birth and death processes (density-dependence included)
Local catastrophes (environmental stochasticity)
Global dispersal towards a dispersal pool and partial settlement (costs of dispersal)
Casagrandi & Gatto. Nature 1999
A mesoscale approach of metapopulation dynamics
Casagrandi & Gatto. Nature 1999
Introducing habitat heterogeneity
The source-sink model (Pulliam)
Productive habitats
Non-productive habitats
Source : net exporter of migrants (high productivity)
Sink : net importer of migrants (low productivity)
The simple source sink-models predict that
Absolute sinks would not persist in the absence of sources
A large proportion of a population can exist in sink habitats
In the case of density-dependent regulation
Sinks are set above their carrying capacity
Sources are set below their carrying capacity
Asymmetric migration between habitat patches (unbalanced dispersal)
Pulliam. Am. Nat. 1988.
Towards more explicit approaches: incidence models
The metapopulation model
discrete spatial structure
two spatial scales (local and regional)
local persistence for at least a few generations
dominant effects of extinction-colonisation dynamics
Hanski’s metapopulation model : incidence functions
« occupancy » models designed for butterflies populations
extinction rate depends on patch area
colonisation rate depends on size of and distance to neighbouring patches
State variable : occupancy of a given patch i
Model parameters and incidence functions
E = min[e/Ax,1] → extinction rate decreases with patch area
C = β ∑ exp(-α dij) pj Aj → colonisation decreases with distance and increases with crowding and area
Hanski. Metapopulation ecology. 1999.
App1 : the rescue effect and alternative equilibria
Very low metapopulation occupancy = negative metapopulation growth rate due to low
colonization rate
Higher occupancy = higher colonization rate (rescue effect) favors increased growth rate
Very high occupancy = crowding and population regulation at the regional level
Predicted (theory)
Observed (66 networks)
Predicted (empirical model)
Hanski. Nature. 1998.
App2 : metapopulation viability analysis
Metapopulation of 20 habitat patches
monitored by MRC techniques during 10
years
Design of a spatially explicit metapopulation
model based on field data assuming (1) local
density-dependence, (2) dispersal between
sites and (3) spatial correlation of local
dynamics
Schtickzelle & Baguette. Oikos 2004
App2 : metapopulation viability analysis
Local density-dependence based on a logistic
growth model, carrying capacity increases
with patch size
Large (significant) effects of climate
conditions on population growth modeled
by a stochastic component
Significant spatial autocorrelation of
population growth rates fitted by a negative
exponential function (most correlations
occur at scales below 1000 m)
Virtual model for dispersal assuming a
decrease of dispersal with distance and some
fat-tail dispersal kernel
Schtickzelle & Baguette. Oikos 2004
App2 : validation of the metapopulation model
Schtickzelle & Baguette. Oikos 2004
App2 : sensitivity analysis
Simulation time : 200 years
1000 simulations
Calculation of quasiextinction risk
Schtickzelle & Baguette. Oikos 2004
App2 : scenario analysis
Simulation time : 200 years
1000 simulations
Calculation of quasiextinction risk
Scenario 1a: management by grazing (which reduces short-term suitability) with upper damage
Scenario 1b: management by grazing (which reduces short-term suitability) with lower damage
Scenario 2: effect of an increase of mean temperature of + 2°C
Scenario 3: combined effects of land use (scenario 1b) and climate change
Schtickzelle & Baguette. Oikos 2004
Contrasted effects of habitat destruction: small scale
experiment
No community scale response due to a large
variation in species-specific responses
3 common
small
mammals
(from large
to small)
snakes
Robinson et al. Science. 1992.
Clonal / Non-clonal plants
Habitat destruction and species decline: large
scale experiment
Large-scale experimental habitat destruction experiment in Brasil
(13 years, 23 patches)
12 pristine forest patches
11 isolated patches from 10 to 600 ha
Monitoring of the bird community and analysis with a statistical
model of patch turnover in species presence/absence
Extinction rate estimated according to the « best » statistical model
Ferraz et al.. Science. 2007.
Habitat destruction and species decline: large
scale experiment
Positive effect of fragmentation on extinction rates,
but results are highly variable and many species
are insensitive to habitat fragmentation
Negative effect of patch size on extinction rate
Ferraz et al.. Science. 2007.
Contrasted effects of habitat fragmentation: why ?
Details that can matter
Landscape structure : corridors and matrices, spatial scale
Behavioural flexibility : context-dependent dispersal
Community processes : species interactions (e.g. competition-colonization trade-off,
functional complementarities, trophic interactions …)
Case example: behavioural plasticity in dispersal
Density-independent dispersal = causes some rescue at low population density but
tends to synchronize local population dynamics (spatial autocorrelation, also called
Moran’s effect)
Negative density-dependent dispersal = precipitates population extinction (dispersal
through conspecifics attraction) but tends to limit spatial synchronization
Positive density-dependent dispersal = increases the rescue effect at low population
density (dispersal through colonization) but tends to increase spatial synchronization
Behavioral plasticity in dispersal
Field experiments with root voles (Microtus oeconomus) in Norway = fence effects with less local dispersal at
high population densities
Andreassen et al. Proc. Roy. Soc. 2005.
Testing for metapopulation theory
Legrand et al. Nat. Methods. 2012.
Testing for metapopulation theory
Legrand et al. Nat. Methods. 2012.
Evolutionary consequences of habitat
fragmentation and the rescue effect
Levels of selection in fragmented populations
Selection within demes (intrademic selection)
social interactions
kinship structures
Selection between demes (interdemic selection)
dispersal and colonisation
migration and founder effects
« Metapopulation effect » Olivieri and Gouyon 1997.
Examples of antagonistic selective pressures
Cooperative behaviour in mammals = selected for between demes but counterselected within each deme
Dispersal in plants = counterselected within the deme but selected between demes
Virulence in parasites = selected for within the deme but can be selected against between demes
Habitat fragmentation causes selection due
Genetic heterogeneity : inbreeding and kinship structure.
Demographic heterogeneity : e.g. density-dependence.
Environmental heterogeneity : e.g. habitat quality.
Evolution of dispersal rate : kin selection
Basic assumptions
homogeneity in deme sizes
homogeneity in deme structures
kin selection due to genetic heterogeneity
Interactions with
Philopatry
Dispersal
Relatives
Many
Few
Conspecifics
Some
Some
Kin competition
Dispersal
Hamilton & May Nature. 1977
Kin cooperation
Philopatry
Perrin & Goudet. Oxf Univ Press
2001
Evolution of dispersal rate : demographic
heterogeneity
Basic assumptions
no kinship structure
variance in patch occupancy due to local extinction
selection due to demographic heterogeneity (avoidance of competition)
Model of successional dynamics and plant dispersal
More colonization opportunities
Fast succession
Less local competition
Slow succession
Ronce et al. Am Nat. 2000.
Evolution of dispersal rate : environnemental
heterogeneity
Basic assumptions : habitat heterogeneity
selection due to environmental heterogeneity
two traits : dispersal and local adaptation traits
Habitat variation alone – two habitats - no kin selection
local maladaptation = cost of dispersal = loss of migration
local adaptation = benefits of specialization = evolution of specialist strategies with two
non-dispersive specialist strategies inside each habitat
Habitat + temporal variation - no kin selection
temporal variation = risk spreading benefits = evolution of partial migration
co-evolution of local adaptation can lead to various patterns of existence and
coexistence between the two non-dispersive specialists and a generalist dispersive
strategy
Kisdi. Am Nat. 2002.
Evolution of plant dispersal on islands
« Mainland »
« Island »
Comparative analysis of dispersal abilities for two plant
species based on morphological measurements
The loss of migration abilities is a common evolutionary
syndrome of island species / populations
Cody and Overton. J. Ecol. 1996
Evolution of flight behaviour in butterflies
« Woodland » butterflies
Raised in a common garden and
investigated for their flight
behaviour in the laboratory
« Agricultural » butterflies
Pararge aegeria
Observed differences between the fragmented and non-fragmented landscapes:
• females from woodland habitats travel longer distances per unit time
• females from woodland habitats cross more often boundary
• females from woodland habitats more often seen at flight
• females from woodland habitats traverse more often between their preferred habitats
• males from woodland do not differ from male from agricultural landscapes
Conclusion
Observed differences restricted to females
Counter-selection of dispersal behaviour in females from agricultural landscapes
Merckx et al. Proc. Roy. Soc. London 2003
Dispersal behaviour and landscape structure
in spiders
Isolated
Connected
Continuous
Raised in a common garden and
investigated for the « tip-toe »
behaviour in the laboratory
Passive dispersal seems to be
selected against in more
fragmented habitats !
This can be explained by dominant
effects of the cost of dispersal or
some form of habitat specialization
Bonte et al. Anim. Behav. 2006
Dispersal and habitat specialization in different
spider species
Intensity of « tip-toe » behavior indicates passive dispersal ability
Dispersive species are habitat generalists → dispersal
may be counterselected in isolated landscapes due to
habitat specialization
Index of habitat
specialization based on
local recordings and
literature review in Europe
Bonte et al. Proc. Roy. Soc. Lond. 2003
Evolutionary rescue (or suicide) ?
Ferrière and Legendre Phil.. Trans. Roy. Soc. Lond 2011
References
Colas B. et al. 2004. Adaptive responses to landscape disturbances: empirical evidence. Pp. 284-289
in Evolutionary Conservation Biology (eds. Ferrière et al.). Cambridge University Press.
Fahrig, L. 2003. Effects of habitat fragmentation on biodiversity. Annual Review of Ecology and
Systematics. 34:487-515.
Ferraz, G. et al. 2007. A large-scale deforestation experiment: effects of patch area and isolation
on Amazon birds. Science 315:238-241.
Le Galliard, J.-F., Ferrière, R. and J. Clobert. 2003. Mother-offspring interactions affect natal
dispersal in a lizard. Proceedings Royal Society London B 270:1163-1169.
Hanski I. 1998. Metapopulation dynamics. Nature 396:41-49.
Hanski I. 1999. Metapopulation ecology. Oxford University Press.
Ronce and Olivieri. 2004. Life history evolution in metapopulations. Pp. 227-257 in Ecology, Genetics
and Evolution of Metapopulations (eds. Hanski and Gagiotti). Elsevier.