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.