2009 Reports Re Connectivity

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FORUM

Climate change, connectivity and conservation

decision making: back to basics

Jenny A. Hodgson*1, Chris D. Thomas2, Brendan A. Wintle3 and Atte Moilanen4

1Institute of Integrative & Comparative Biology, Miall Building, University of Leeds, Leeds LS2 9JT, UK; 2Department

of Biology, University of York, PO Box 373, York YO10 5YW, UK; 3School of Botany, University of Melbourne, Victoria

3010, Australia; and 4Metapopulation Research Group, Department of Biological and Environmental Sciences, PO

Box 65 (Viikinkaari 1), University of Helsinki, Helsinki FI-00014, Finland

Summary

1. The challenge of climate change forces us to re-examine the assumptions underlying conserva-

tion planning.2. Increasing connectivity has emerged as the most favoured option for conservation in the face of

climate change.

3. We argue that the importance of connectivity is being overemphasized: quantifying the benefits

of connectivity per se is plagued with uncertainty, and connectivity can be co-incidentally improved

by targeting more concrete metrics: habitat area and habitat quality.

4. Synthesis and applications. Before investing in connectivity projects, conservation practitioners

should analyse the benefits expected to arise from increasing connectivity and compare them with

alternative investments, to ensure as much biodiversity conservation and resilience to climate

change as possible within their budget. Strategies that we expect to remain robust in the face of

climate change include maintaining and increasing the area of high quality habitats, prioritizing

areas that have high environmental heterogeneity and controlling other anthropogenic threatening

processes.

Key-words: adaptation, biodiversity, conservation prioritization, habitat quality, landscape

planning, spatial ecology, speciesarea relationship, uncertainty

Introduction

How should we adapt our conservation strategies in the face of

climate change? Of the multitude of suggested answers, the

single most repeated suggestion is to increase connectivity

(Heller & Zavaleta 2009). Connectivity conservation (Crooks

& Sanjayan 2006) is gathering pace and political support (e.g.Australian Government 2004; IUCN WCPA 2006; Kettunen

et al. 2007). The idea is to maintain and build connected envi-

ronments that will enable species to move with the climate.

Whilst laudable, our concern is that this strategy could cause

more harm than good if it inadvertently redirects resources

and attention away from more certain and effective conserva-

tion actions.

In this study, we revisit the principles of spatial ecology

and conservation planning. We summarize how connectivity

emerges as a complicated function of habitat area, habitat

quality, the spatial arrangement of habitat and species-spe-

cific dispersal. We argue that uncertainty associated with

connectivity is generally higher than uncertainty about habi-

tat area and quality, and threatening processes such habitat

destruction. We aim for a more balanced approach to devel-

oping climate change conservation strategies where connec-

tivity is treated as a potentially useful tool, but not as an end

in itself.

Spatial conservation planning: the basics

We start from a consideration of individual species; the popu-

lation theory we discuss applies to any species, but we apply

this primarily to spatial planning for terrestrial landscapes.

The regional carrying capacity, and hence the population size

of a species depends principally on the area of suitable habitat,

the quality of that habitat and on the spatial arrangement

of suitable habitat (Fig. 1; Andrewartha & Birch 1954; Mac-

Arthur & Wilson 1967). Habitat arrangement has multiple

dimensions, but we consider the main one to be aggregation

(Fig. 1); how habitat is concentrated in space. We consider

habitat quality to be a measure of potential population*Correspondence author. E-mail: [email protected]

Journal of Applied Ecology 2009, 46, 964969 doi: 10.1111/j.1365-2664.2009.01695.x

2009 The Authors. Journal compilation 2009 British Ecological Society


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growth andor density, and area to be the total area with a

positive quality. Importantly, each of these three quantities has

a threshold below which the regional population of the species

will not persist (Fig. 1) too little habitat area, too low habitat

quality or excessive dispersion of habitat will all lead to regio-

nal extinction of the focal species (Fig. 1; With & King 1999;

Hanski & Ovaskainen 2000). Eventhough area, habitat quality

and aggregation are abstractions and their exact definitions

might be debated, there is very good evidence for their effects

on single species (e.g. Thomas, Thomas & Warren 1992), and

they are used as thebasis of much conservation planning(Mar-

gules & Pressey 2000; Moilanen & Wintle 2006).

Defining area, quality and aggregation for multiple species

simultaneously is not straightforward because the require-ments of species vary. The relationship between species and

area is most strongly established (MacArthur & Wilson 1967;

Simberloff 1976a,b). More area generally means more individ-

uals, more resources and more environmental variation, giving

opportunities for niche specialization. Quality is a difficult

notion when considering multiple species, but for practical

purposes can be described in terms of freedom from anthropo-

genic degradation, disturbance, pollution, etc. Influences of

habitat aggregation and isolation on diversity are seen for

many communities (e.g. MacArthur & Wilson 1967; Simberl-

off 1976b; Hanski 1998), but differences among species in their

habitat requirements and dispersal characteristics mean thatthere is no universal relationship.

Connectivity and uncertainty

Connectivity is seen as something that should be accounted

for in conservation planning (Margules & Pressey 2000;

McCarthy, Thompson & Possingham 2005; Moilanen et al.

2005), but there are numerous overlapping definitions

(Tischendorf & Fahrig 2000; Moilanen & Hanski 2001;

Goodwin 2003; Fagan & Calabrese 2006). Broadly, func-

tional connectivity estimates the actual or potential rate of

immigration into a point, cell, or patch on the landscape

(Hanski 1998; Tischendorf & Fahrig 2000), and thus depends

on several attributes of the species, as well as the interaction

between the species and the landscape (Fig 2). As a result,

most connectivity measures subsume influences of habitat

area, quality and spatial aggregation, and some also include

information about heterogeneities in the non-habitat (Fig. 2).

We argue that uncertainties in the estimation and effects of

connectivity make it potentially inefficient as a primary conser-

vation metric. Conservation planning is plagued with uncer-tainties (Regan, Colyvan & Burgman 2001). Uncertainty

about area and quality derive from uncertainty about which

environmental and biotic factors explain the local carrying

capacity for a given species (Elith, Burgman & Regan 2002).

Uncertainty about the functional connectivity of the species

automatically includes uncertainties relating to area, quality

and habitat pattern because functional connectivity depends

partly on the distribution and quality of habitats in the land-

scape (Fig. 2). Additional uncertainties about the measurement

of connectivity include: species-specific influences of distance

on dispersal; tails of dispersal distributions, which are notori-

ously difficult to estimate; effects of source and target habitatquality on emigration and immigration; how dispersing indi-

viduals search for habitat; how movement behaviour is

affected by the spatial structure of non-habitat, and the influ-

ence of spatially correlated environmental stochasticity on

population-dynamical processes (Moilanen & Nieminen

2002). By combining all of these, uncertainty about measuring

and predicting connectivity is always higher than uncertainty

about the constituent factors that contribute to connectivity.

Not only is the measurement of connectivity uncertain, but

so are its effects on long-term expected population size. Total

carrying capacity always steadily increases with increasing

habitat area and quality, but does not do so with increasing

habitat aggregation (Fig. 1bd) or increasing dispersal, theother components of connectivity. There is only a relatively

narrow window at intermediate levels of habitat aggregation

where increased aggregation makes a major difference to

expected population size (because once habitats are close

enough to be colonized, further benefits of aggregating habitat

or increasing dispersal are diminished). Thus, increasing area

and quality are more certain to increase population size than

are increases in aggregation and dispersal, unless isolation is

already known to be the main constraint for a particular

species and landscape.

As uncertainties about connectivity tend to be high, and

increases in habitat quantity and quality coincidentallyimprove connectivity, we conclude one should generally

(a) (b)

(c) (d)

Fig. 1. Fundamental variables of spatial population biology. (a)

Habitat area, habitat quality and habitat aggregation (see text for

definitions) are independent axes that all affect regional population

size (they also affect functional connectivity, see Fig. 2). (bd) For

each factor, there is a threshold below which the regional popula-

tion is unable to persist. Solid lines indicate potential carrying

capacity, whilst dashed lines denote the long-term expected popula-

tion size.

Climate, connectivity and conservation 965

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provide higher weight in decision-making to actions that

increase area and quality. Theoretically, we know that popula-

tions will sometimes benefit more from a small, well-connected

piece of habitat than a larger, more isolated one, but the rela-

tive uncertainties and the probability of worse-than-expectedoutcomes should also affect our decision making. From a deci-

sion theoretic perspective, when faced with two options that

convey similar expected (mean) returns, one should choose

the option with the lowest variance of expected outcome to

maximize the probability of achieving ones conservation goal

(e.g. Ben-Haim 2001).

We are particularly concerned that in a planning process,

people who want to release areas from conservation, e.g. for

development, could actually exploit the profusion of connec-

tivity measures (Kindlmann & Burel 2008) to choose one that

works for them (Walker et al. 2009). For example, restored

corridors, stepping stones or softening of the anthropogenic

matrix will cause increases in some connectivity measures.

Depending on the connectivity metric used, a large percentage

increase in connectivity could be used to argue that a large

percentage decrease in habitat area is acceptable allowing a

development to proceed. Loss of habitat implies certain and

immediate decreases in population sizes, whereas compensat-

ing long-term benefits of additional connectivity might be lar-

gely unknown and possibly small (Falcy & Estades 2007).

Notwithstanding these misgivings, the functional connectiv-

ity of landscapes applied to single species is a very useful con-

cept in appropriate circumstances, when the constraints on a

particular species are known. But, ultimately, conservation is a

multi-species enterprise. In this context, various measures ofstructural connectivity have been proposed, that generalize

the connectivity of vegetation types without reference to partic-

ular species. Combining species responses in this way magni-

fies uncertainty because multi-species responses are not a

simple function of each individual species response. There is

an attractive simplicity to increasing structural connectivity formulti-species conservation, but the scientific basis for such a

strategy is largely absent and the applicability of this concept

under climate change is also highly uncertain. The trade-off

between increased structural connectivity per se and increased

protection for existing natural or semi-natural habitats are

always very difficult to calculate. However, maintaining and

increasing the area of natural or semi-natural habitats will add

useful habitat area for many species and, as described above,

will usually coincidentally increase connectivity.

The new world order

So far, our discussion has been most relevant to situations

where the regional distributions of species can be assumed to

be relatively stationary. Given climate change and the lagged

responses of species (Mene ndez et al. 2006), dynamic change

will be the norm for the foreseeable future. At large scales there

are shifts to higher latitudes and elevations (Hickling et al.

2006; Parmesan 2006; IPCC 2007) andmovements along mois-

ture gradients, and at smaller scales there are shifts in preferred

microclimates and changes to the nature of the vegetation that

constitutes habitat (Thomas et al. 2001; Davies et al. 2006).

These changes undermine three common presumptions in

conservation planning. First, we often presume that vegetation

type can be used as a reasonable proxy for habitat availabilityfor one or many species. Quaternary evidence shows that

Habitat

What the

organism needs

(niche)

defines

Area Quality Aggregation

(or other pattern)

Dispersal

mechanism, etc.

Potential forbarriers or

conduits in non

habitat

Connectivity (proxy for

immigration rates)

Vital rates and

carrying capacity

Population size, spatial distribution and

persistence probability

is quantified in terms of

Fig.2. A schematic of the place of (func-tional) connectivity in spatial ecology and

conservation. Functional connectivity is a

quantity that always incorporates some

aspect of spatial pattern, but it usually also

includes information about the amount and

quality of habitats and factors influencing

dispersal behaviour and success.

966 J. A. Hodgson et al.



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species exhibit individualistic responses to climate change, and

vegetation types change with the climate (Williams, Shuman &

Webb 2001), so that the community classification schemes we

now use to describe vegetation types will become redundant in

the long term. Secondly, we assume that structural connectiv-

ity, measured on the basis of land cover types, is a reasonableproxy for functional connectivity of multiple species. As with

the first assumption, this will become less reasonable the more

climate change advances and changes communities.

Thirdly, we commonly assume that protecting locations

with the most populations of a species will maximize the

chances of persistence in both the short- and long-term sur-

vival. Under climate change, prioritizing only existing core

populations carries the danger of promoting short-term per-

sistence in current strongholds at the expense of long-term

survival; but prioritizing only marginal populations that are

predicted to expand is risky because of massive uncertainties

about the true consequences of climate change. In essence

we are required to deal with trade-offs through time, as well

as continuing to pay attention to trade-offs in space and

trade-offs between species. We have to address the addi-

tional question How much short-term conservation success

should we forgo in order in increase the long-term probabil-

ity of achieving our targets? Perhaps not much, as benefits

that are to materialize a long time in the future may have a

tendency of disappearing on the way (Walker et al. 2009).

Such considerations need to be incorporated within popula-

tion viability analyses and decision frameworks, which can

no longer assume long-term stasis in environmental condi-

tions.

Reasons to be cheerful

It is easy to be overwhelmed by the complexity and uncertainty

involved in conservation planning for a world with climate

change. There is a huge desire to do something but what

exactly is it that we should do? A vast number of suggestions

have been made, and there is limited direct evidence to assess

which of these is likely to be most effective (Heller & Zavaleta

2009). So, can we step back and ask if any principles hold true

with or without climate change, and thereby which conserva-

tion strategies are most likely to be robust?

One such principle is that increasing numbers of species areassociated with increasing area (Connor & McCoy 1979; Guil-

haumon et al. 2008). But how much area is enough? Effective

conservation requires sufficient habitat where a species cur-

rently occurs and additional locations that will support popu-

lations whilst the distribution is changing, until it reaches a

new equilibrium (assuming the climate does; Araujo et al.

2004). Any previously used target [e.g. the 10% terrestrial pro-

tected area target (IUCN 2004)] will deliver lower conservation

outcomes under climate change than originally hoped. There-

fore, renewed effort and additional funding to conserve extra

land is warranted. Locations that have low human impacts

should remain good for many species, even if the identities of

those species change. Maintaining sites of high value to biodi-

versity should be feasible, but management that attempts to

retain a particular community composition may be expensive

and ultimately doomed to failure.

A second generalization is that environmental heterogeneity

provides opportunities for populations to survive different

extremes by shifting between different types of vegetation,

soils, aspects or elevations (Thomas et al. 2001; Davies et al.2006). Species diversity and endemism are also increased in

regions with high topographic and habitat diversity (e.g. Sim-

berloff 1976a), especially where there are steep elevation and

climatic gradients (Ohlemu ller et al. 2008). Our second mes-

sage is that focussing efforts on regions with high existing envi-

ronmental heterogeneity is likely to be a robust strategy. In a

sense, we are identifying the importance of a different kind of

connectivity that between cooler and warmer (and drier and

moister), habitats rather than between currently similar habitats.

Further research is needed to quantify the benefit of habitat

diversity, especially when there might be a trade-off between this

and theaggregation of existing habitat for many species.

Thirdly, the majority of small-range terrestrial species are

clustered into a small percentage of the land surface (centres of

endemismareas of high irreplaceability, cf. Wilson, Carwar-

dine & Possingham 2009), many of which are mountain

ranges. A high percentage of thespecies threatened with extinc-

tion from climate change are found in such locations: they are

expected to show range retractions within the regions where

they currently occur, and are unlikely to achieve long distance

colonization of other parts of the world (Midgley et al. 2002;

Williams, Bolitho, & Fox 2003; Thomas et al. 2004; Malcolm

et al. 2006; Ohlemu ller et al. 2008).So, our third message is that

concentration of conservation effort in centres of endemism

remains a valid strategy.Fourthly, almost all threatened species are negatively

impacted by multiple factors. In some instances, mitigating

known threats other than climate change may be sufficient to

permit a population to persist, even if the local climate has

deteriorated. When this strategy cannot ensure persistence in

its own right, mitigating known threats should be regarded as

an essential first step in making populations robust to climate

change. We recommend dealing with known (stoppable)

threats for which there are known solutions before addressing

uncertain andor unstoppable threats with less certain or less

feasible solutions (Pressey et al. 2007; Wilson et al. 2007).

These four principles, increasing protected area, maintain-ing and in some cases increasing environmental heterogeneity,

concentrating efforts in centres of endemism, and reducing

other pressures are likely to be beneficial and robust, with or

without climate change. However, these are rules of thumb,

and there is great potential for improved planning at regional

scales with improved adaptive decision-making methods.

Importantly, decision-making tools need to weight strategies

according to their relative costs, expected benefits and the

uncertainty in achieving that benefit (Burgman, Lindenmayer

& Elith 2005; McDonald-Madden, Baxter & Possingham

2008). Ecological research needs to contribute by quantifying

benefits (including the benefits of connectivity and the bene-

fits of habitat heterogeneity) in terms of a common currency,

e.g. long-term species persistence, and by quantifying




5/16

uncertainty. Research is required in the development of deci-

sion frameworks (Hoegh-Guldberg et al. 2008) to integrate

and visualize the costs and benefits, and to ensure that meth-

ods are easy to adapt and update as new information

becomes available.

Conclusion

In summary, we think that the political and ecological reality

of climate change should prompt us to reassess which ideas to

keep, which to modify and which to abandon (Table 1). Con-

nectivity usefully reminds people that excessive isolation is a

threat to populations, but, as increased attention is paid to the

spatial arrangement of habitats and dispersal, morefundamen-

tal issues may be overlooked (Fig. 1; Table 1). Whilst climate

change adds extra challenges, potential damage can still be

alleviated by removing other sources of threat. Land conver-

sion and land-use change leading to habitat loss is still the most

cited threat to currently endangered species, and the most

straightforward way to tackle this is to maintain and restore

larger areas of natural habitat. Species will not be able to sur-

vive where they are or shift their distributions to new climati-

cally suitable areas unless there are sufficient habitats for them,

and it should be remembered that increasing habitat area is an

effective way of increasing connectivity. Furthermore, con-

serving habitats will be beneficial even if the particular species

found in an area are graduallyreplaced by others as the climate

changes. The conservation of high quality existing habitats

should therefore remain the primary focus of conservation

efforts to maintain biodiversity.

Acknowledgements

Thanks to two anonymous reviewers whose comments helped to improve the

manuscript. J.H. and C.D.T. were supported by Natural England. B.W. was

supported by the Australian ResearchCouncil (DP0774288)and the Australian

Governments Commonwealth Environment Research Facility program. A.M.

was supported by the Academy of Finland, Finnish Center of Excellence Pro-

gramme2006-2011, grant213457.

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Table1. Suggested re-assessment of basic ideas in conservation planning, assuming climate change

Ideas to keep Ideas to modify and develop Ideas that hold us back

More total area is beneficial; including

expanding present conservation areas

Biodiversity hotspotscentres of endemismshould be prioritized

Environmentalhabitat heterogeneity

facilitates diversity and persistence

Human activities that diminish diversity

should be minimized or reversed

The time frame for conservation planning (the

trade-off between current and future benefit;

and incorporation of environmentalchange in population viability assessment)

The role of connectivity, including trade-offs

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conservation actions

Attempting to maintain existing or

past community composition

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Received27 February2009;accepted3 July2009HandlingEditor: Morten Frederiksen




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FORUM

Connectivity, dispersal behaviour and conservation

under climate change: a response to Hodgson et al.

Veronica A. J. Doerr1,2*, Tom Barrett3 and Erik D. Doerr1,2

1CSIRO Ecosystem Sciences, GPO Box 284, Canberra ACT 2601, Australia; 2Research School of Biology, Australian

National University, Canberra ACT 0200, Australia; and 3New South Wales Department of Environment, Climate

Change & Water, PO Box 494, Armidale NSW 2350, Australia

Summary

1. Hodgson et al. [Journal of Applied Ecology 46 (2009) 964] argue that connectivity is complex and

uncertain, that it can be improved incidentally by increasing habitat extent, and that connectivity

conservation is unlikely to be effective under climate change.2. We believe that they have overlooked recent research on dispersal behaviour and structural con-

nectivity, which has improved our understanding of functional connectivity and revealed that it will

not necessarily increase with habitat extent.

3. New modelling techniques including least-cost path models incorporate this more detailed

understanding of connectivity into conservation planning, facilitating the true aim of connectivity

conservation to ensure appropriate interactions between habitat extent, quality and connectivity.

4. Synthesis and applications. Advances in behavioural research and modelling techniques allow us

to manage structural connectivity with as much certainty as we manage extent and quality of habi-

tat. Successful landscape conservation to address both current threats and future climate change

must manage these three elements in concert.

Key-words: aggregation, behavioural ecology, connectivity conservation, corridor, fragmen-tation, gap-crossing, metapopulation, population viability, range shift, stepping stone

Introduction

For most of the worlds ecosystems, human-induced habitat

loss, degradation and fragmentation are primary causes of

declines in biodiversity (Fahrig 2003; Lindenmayer & Fischer

2006). Furthermore, climate change is predicted to interact

with and intensify the effects of these problems. Connectivity

conservation has emerged as an overarching solution with

considerable political and popular support (Crooks & Sanja-

yan 2006). However, Hodgson et al. (2009) highlight the dan-

gers of investing in connectivity per se, and argue that other

strategies may provide better protection for species in a chang-

ing climate.

We wholeheartedly agree with Hodgson et al. that connec-

tivity should not be the sole focus of conservation actions, and

that conservation investments should be based on analysis of

their likely benefits. Yet Hodgson et al. suggest that connectiv-

ity conservation is never likely to be a robust strategy, and here

we disagree. Specifically, Hodgson et al. argue that there is too

much uncertainty surrounding connectivity, that connectivity

is primarily a result of habitat aggregation, and it can coinci-

dentally be improved by increasing habitat extent. They also

suggest that connectivity conservation sacrifices long-term

conservation success under a changing climate in favour of

short-term gains. In this response, we suggest that Hodgson

et al. have overlooked recent advances in our understanding of

connectivity, particularly arising from research on dispersal

behaviour. These advances provide a clearer distinction

between structural and functional connectivity and greater cer-

tainty regarding the effects of structural connectivity. They also

bring a new awareness that increases in habitat extent alone

will not necessarily increase functional connectivity. In addi-

tion, we believe that Hodgson et al. have misinterpreted con-

nectivity conservation, which carries a specific meaning that

involves more than just conserving structural connectivity, and

can provide long-term solutions to many of the threats associ-

ated with climate change including those highlighted by Hodg-

son et al. Finally, we suggest that the differences in our

perspectives may partly result from differences in the scales at

which empirical research and conservation planning are con-

ducted. Fortunately, new modelling techniques are allowing us*Correspondence author. E-mail: [email protected]


2010 The Authors. Journal of Applied Ecology 2010 British Ecological Society


8/16

to move beyond simple measures of aggregation to incorporate

a more detailed behavioural understanding of connectivity into

conservation planning, despite differences in scale.

Dispersal behaviour and structural

connectivity

The intent of connectivity is to facilitate dispersal of individu-

als. Thus, an empirical understanding of connectivity depends

on understanding animal behaviour, particularly movement

and dispersal behaviour, to reveal what parts of landscapes

individuals are willing to move through and why (Lima & Zoll-

ner 1996; Chetkiewicz, Clair & Boyce 2006). The value of

behavioural research for conservation has been debated

(Blumstein & Fernandez-Juricic 2004; Caro 2007), and thus it

is unsurprising if conservation biologists are not familiar with

the movement behaviour literature, very little of which existed

during early discussions about connectivity. Yet movement

behaviour is a rapidly growing field (Nathan 2008), with exten-

sive empirical analyses and emerging theories that can provide

a strong foundation for modelling and conserving connectiv-

ity.

When connectivity began to be viewed from a behaviour-

based perspective, it became a characteristic of the matrix

between subpopulations (Taylor, Fahrig & With 2006), rather

than a characteristic of patches or landscapes. Movement

could be dependent not just on distances between subpopula-

tions (i.e. aggregation) but on the physical characteristics of

the matrix itself, particularly the presence of habitat elements

too small for settlement but which might nonetheless facilitate

movement. As a result, a much clearer distinction emergedbetween structural and functional connectivity. Structural

connectivity refers to physical characteristics of the landscape

between patches of occupied habitat. Functional connectivity

refers to the degree to which movement of individuals andor

their genetic material actually occurs, and is influenced by both

movement potential due to structural connectivity and by local

subpopulation dynamics (Hilty, Lidicker & Merenlender

2006).

Empirical research on movement behaviour has concen-

trated on revealing what types of structural connectivity pro-

vide the potential for dispersal movements and thus contribute

to functional connectivity. A number of studies have shownthat various species use corridors to move through fragmented

landscapes (Haddad et al. 2003; Haddad & Tewksbury 2005),

and some have demonstrated the use of simpler landscape ele-

ments such as scattered trees (Fischer & Lindenmayer 2002;

Doerr, Doerr & Davies 2010). Research on gap-crossing

behaviour has been particularly critical, identifying gap dis-

tances either within corridors or among scattered trees that

may prevent movements, thus revealing details of structural

connectivity that contribute to movement potential (St. Clair

et al. 1998; Grubb & Doherty 1999; Robertson & Radford

2009). In addition, research on overall movement strategies

such as foray search is illustrating that distances between

subpopulations (i.e. aggregation) may have a threshold effect

rather than a linear effect on movement potential. When

individuals use a foray-based search strategy, they may have a

maximum search distance beyond which they will not travel,

regardless of how much structural connectivity is present in the

landscape (Conradt, Roper & Thomas 2001; Doerr & Doerr

2005; Doerr, Doerr & Davies 2010).

The species-specific nature of behavioural research may beviewed as an impediment to its usefulness for ecosystem con-

servation, but patterns are emerging which suggest that

responses to structural connectivity may not be as species-spe-

cific as was once thought (Haddad et al. 2003; Doerr, Doerr &

Davies 2010; Gilbert-Norton et al. 2010). Instead, movement

behaviour may be shaped by the structure of environments

experienced over evolutionary time, and species in any given

ecological community with broadly similar life-histories may

have evolved similar movement behaviours as responses to

their shared environments (Fahrig 2007). For example, Doerr,

Doerr & Davies (in press) found that use of scattered trees,

foray distances, and gap distances crossed were similar among

five Australian woodland birds despite substantial differences

in their ecology. Belisle (2005) proposed that travel costs may

provide one mechanism through which landscapes can exert

similar evolutionary pressures across species. Thus, theories

from behavioural ecology such as the marginal value theorem

could provide the basis for general theories of connectivity,

allowing us to predict the effects of different types of structural

connectivity for large suites of species at once (Belisle 2005).

Conservation certainty

All of these advances are making structural connectivity a

much more measurable and manageable concept than Hodg-son et al. suggest. Functional connectivity remains complex

because it integrates movement potential with the dynamics of

subpopulations (which is why Hodgson et al. deem it too

intractable for conservation planning). Yet structural connec-

tivity contributes significantly to functional connectivity by

determining movement potential. The resulting effects on pop-

ulation persistence are also increasingly predictable thanks to

controlled research in experimental landscapes which is dem-

onstrating that connected patches experience fewer local

extinctions than isolated patches (Damschen et al. 2006; Brud-

vig et al. 2009). Thus, structural connectivity can be directly

quantified in the landscape, has predictable effects onmovement potential, and is known to contribute to population

persistence, making it a worthwhile focus for management.

Unfortunately, Hodgson et al. omit structural connectivity

from their schematic of the place of connectivity in conserva-

tion (Hodgson et al., Fig. 2). We have revised their diagram to

distinguish between structural and functional connectivity and

depict the relationships between them, as well as relationships

with the area and quality of habitat suitable for settlement

(Fig. 1). Structural connectivity is independent of habitat area

and quality and is what defines habitat for dispersal, just

as area and quality are what define habitat for settlement.

Structural connectivity, habitat area and quality interact to

determine functional connectivity, but they also interact

to determine subpopulation dynamics and thus the effective

144 V. A. J. Doerr, T. Barrett & E. D. Doerr

2010 The Authors. Journal of Applied Ecology 2010 British Ecological Society, Journal of Applied Ecology, 48, 143147


9/16

population size of the population as a whole. None has a direct

influence on populations completely independent of the others

all provide the same degree of conservation certainty because

their benefits depend on the interactions between them.

Hodgson et al. also argue we can be relatively certain about

the positive effects of increasing habitat extent and habitat

quality often assumed to be accomplished through increasingthe size andor number of protected areas. Yet in highly dis-

turbed ecosystems, there may be little habitat left outside of

already existing protected areas. Thus, increasing habitat

extent and improving habitat quality involves restoring habitat

in areas where it has been lost to other land uses. Unfortu-

nately, there are substantial limitations and uncertainties in

our ability to restore ecosystems. For example, nitrogen

enrichment via fertilisation reduces plant diversity as well as

the stability of ecosystems worldwide (McIntyre 2008; Bai

et al. 2010). These effects can last long after fertilisation has

ceased, inhibiting full recovery of the ecosystem despite resto-

ration attempts (Munro et al. 2009). It is also reasonable to

argue that habitat quality will often be more species-specific

than structural connectivity, as habitat for settlement must

provide for many more of a species needs than habitat for

dispersal (Haddad & Tewksbury 2005; Doerr, Doerr & Davies

2010). Restoring habitat for settlement, either for a single

species or particularly for an entire community, may thus be

more complex and uncertain than restoring habitat for

dispersal (i.e. increasing structural connectivity).Finally, Hodgson et al. argue that increasing habitat extent

will coincidentally improve connectivity by increasing aggrega-

tion and thus reducing distances between patches. However,

behavioural research suggests that reducing inter-patch

distances without providing structural connectivity will only

be beneficial once patches become close enough to allow

gap-crossing between them. That distance may be as little as

60100 m (unlikely to be achieved by most efforts to increase

habitat extent), as many species are unwilling to cross gaps any

larger (Desrochers & Hannon 1997; Robertson & Radford

2009; Doerr, Doerr & Davies 2010). Individuals can traverse

much greater distances between habitat patches if structural

connectivity is present, but the existence of foray-based search

means that increases in aggregation may only be beneficial

if distances between patches can be reduced below a critical

foray distance threshold, which may only be 12 km (Doerr,

Doerr & Davies 2010, in press). Thus, the benefits of reducing

aggregation per se (as opposed to managing it in concert with

structural connectivity) are risky because they are not com-

mensurate with effort.

Connectivity conservation is more than just

conserving connectivity

Hodgson et al. interpret connectivity conservation as the effortto increase structural connectivity with the primary purpose of

enabling species range shifts due to climate change. However,

as highlighted above, structural connectivity interacts with

other aspects of the landscape and thus is not necessarily the

sole or most important aspect to improve in every landscape.

Connectivity conservation acknowledges this, and has a very

specific meaning in the literature (IUCN WCPA 2006; Wor-

boys 2010), much like systematic conservation planning has a

specific meaning and doesnt merely refer to taking a system-

atic approach to planning conservation actions (Margules &

Pressey 2000). As a result, connectivity conservation is broader

than Hodgson et al.s interpretation.Connectivity conservation can be defined as coordinated

efforts to achieve metapopulation viability across a range of

spatial scales, which involves evaluating and improving the

interactions between habitatarea, habitat quality and structural

connectivity (Crooks & Sanjayan 2006; Worboys 2010). There

is no overarching rule about which action is always more effec-

tive this depends on the existing conditions in a given land-

scape. Connectivity conservation thus aims to develop flexible

solutions, tailored to the different needs of different landscapes.

This may involve protecting large continuous areas of existing

habitat, but may also involve protecting or increasing connec-

tions between multiple small discontinuous areas of habitat

where that is all that remains. The preference of Hodgson et al.

to focus on habitat area and habitat quality can thus be

What the organismneeds for survival and

reproduction

What the organismneeds for dispersal

Habitat for settlement Habitat for dispersal

DefinesDefines

Is quantified in terms of

Is quantified in terms of

Structural connectivity

Which is the interaction between

Area Quality

Landscape characteristicsbetween areas of habitat

for settlement

Distance between areas ofhabitat for settlement

Potential rates of dispersalbetween subpopulations

Which determine

Functional connectivity (actual rates of dispersal)and

subpopulation size and dynamics

Which interact to determine

Effective population size, spatial distributionand persistence probability

Which are integrated over multiplesubpopulations to determine

Fig. 1. A schematic illustrating the role of both structural and func-

tional connectivity in spatial ecology and conservation (revised from

Fig. 2 in Hodgson et al. (2009)). Functional connectivity results from

interactions between the amount and quality of habitat suitable forsettlement as well as the influence of the rest of the landscape (i.e.

structural connectivity) on the potential for dispersal. Structural con-

nectivity is therefore a vital component of functional connectivity that

is tractableto model andmanage.

Connectivity and dispersal behaviour 145



10/16

encompassed by connectivity conservation wherever these

actions are deemed to provide the greatest benefits.

Finally, the ultimate purpose of connectivity conservation is

not simply to facilitate range shifts, but to increase the resil-

ience of populations to the variety of threats caused by or

intensified by climate change. Under connectivity conserva-tion, structural connectivity is desired where it links multiple

subpopulations via dispersal, allowing subpopulations to func-

tion collectively as one larger, more resilient population. These

principles can be applied at any scale, not just scales that might

be relevant for possible range shifts under climate change

(Opdam & Wascher 2004). Thus, connectivity conservation

can be used to reduce pressures other than climate change, can

be applied to increase viability of populations in centres of

endemism, and can concentrate on areas of high environmen-

tal heterogeneity all of which are principles that Hodgson

et al. suggest will underlie robust conservation strategies under

climate change.

Moving beyond aggregation in large-scale

conservation planning models

Conservation modellers may still be unsure how to incorporate

advances in our understandingof connectivity and connectivity

conservation due to the different scales at which behavioural

research and conservation planning are usually conducted.

Conservation planning often occurs at very large scales

regions to global scales. Yet a behavioural understanding of

connectivity is shaped at scales relevant to movement of indi-

viduals local to landscape scales. The difficulty is that incor-

porating small-scale detail in large-scale models is oftendeemed computationally intractable. Fortunately, there are

promising new advances that can model connectivityover large

spatial scales in ways that align more closely with a behaviour-

based view of connectivity.

First, we have already noted that the types of structural con-

nectivity that facilitate dispersal movements are not necessarily

species-specific. Thus, models may only need to incorporate

general principles (such as threshold distances between habitat

patches) rather than behavioural detail specific to many differ-

ent species. Another way in which conservation planning mod-

els can incorporate a tractable amount of behavioural detail is

through the use of least-cost path modelling and state-spacemodelling. These new types of models simultaneously explore

behavioural and landscape parameters to identify which land-

scape details most need to be incorporated into large-scale

models (Chetkiewicz, Clair & Boyce 2006; Kadoya 2009),

which can then be kept relatively simple by modelling only the

few most relevant small-scale parameters. Remaining compu-

tational challenges can often be overcome by decreasing the

sizes of grid cells only to a relevant scale. Further behavioural

detail can then be incorporated by modelling resistance of grid

cells that have different compositions (McRae & Beier 2007).

One example of the success of these new approaches comes

from our own work, in which data on gap-crossing distances

(Doerr, Doerr & Davies 2010) were used to define the maxi-

mum distance individuals will move through non-habitat, and

data on foray-based search behaviour and foray distances

(Doerr & Doerr 2005; Doerr, Doerr & Davies 2010) were used

to define the maximum distance individuals will move through

structural connectivity, modelled as suboptimal habitat. Using

modern satellite imagery, suboptimal habitat could be mapped

at a fine scale of resolution to detect very small elements ofstructural connectivity known to support dispersal move-

ments, such as single trees. Fine-scale habitat mapping and

simplified behavioural rules were then modelled together using

the least-cost path approach (Drielsma, Manion & Ferrier

2007), with habitat quality as a surrogate for movement cost.

This modelling approach simultaneously evaluates habitat

area, quality and structural connectivity, identifying where

these elements currently exist in concert in the landscape versus

where they are unable to interact due to deficiencies in one or

more elements (Barrett et al. 2010). This gives conservation

planners the ability to make practical recommendations that

maximise the likelihood that actions at a local scale will con-

tribute to population viability and resilience at large scales

(Barrett et al. 2010). These models are currently being used to

guide conservation planning decisions in several regions of

New South Wales, Australia.

Reasons to be cheerful indeed!

As Hodgson et al. suggest, it is easy to be overwhelmed by the

challenges of conservation under climate change. It is worth-

while returning to basic principles, focusing on actions that will

be cost-effective and that will address current threats as well as

those anticipated due to climate change. Fortunately, connec-

tivity conservation provides such an approach by focusing onhabitat area, quality, and structural connectivity as indepen-

dent attributes that must all work together to support viable,

resilient populations. Thanks to a growing body of behavioural

research, we can reliably identify situations in which fostering

structural connectivity in the matrix is likely to yield positive

benefits for populations. We can also use behavioural informa-

tion to model connectivity alongside habitat extent and quality

and thus tailor management to specific landscapes. Ultimately,

these new techniques ensure that large-scale conservation plan-

ning can take advantage of up-to-date connectivity knowledge

to truly provide evidence-based conservation guidance.

Acknowledgements

Thanks to members of the Great Eastern Ranges Initiative, David Westcott,

Paul Sunnucks, Sasha Pavlova, and Colleen Cassady St. Clair for discussions

that shapedthese ideas.The manuscript wasgreatly improvedby thecomments

of Richard Fuller, Sue McIntyre, Dan Lunney, Vicki Logan, and five anony-

mous reviewers.

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Received16 June 2010; accepted20 October2010

HandlingEditor: Morten Frederiksen

Connectivity and dispersal behaviour 147



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FORUM

Habitat area, quality and connectivity: striking the

balance for efficient conservation

Jenny A. Hodgson1*, Atte Moilanen2, Brendan A. Wintle3 and Chris D. Thomas1

1Department of Biology Area 18, University of York, York YO10 5DD, UK; 2Metapopulation Research Group,

Department of Biological and Environmental Sciences, PO Box 65 (Viikinkaari 1), FI-00014, Finland; and 3School

of Botany, University of Melbourne, Vic., 3010, Australia

Summary

1. Population viability can depend on habitat area, habitat quality, the spatial arrangement of habi-

tats (aggregations and connections) and the properties of the intervening non-breeding (matrix)

land. Hodgson et al. [Journal of Applied Ecology 46 (2009) 964] and Doerr, Barrett & Doerr (Journalof Applied Ecology, 2011) disagree on the relative importance of these landscape attributes in

enabling species to persist and change their distributions in response to climate change.

2. A brief review of published evidence suggests that variations in habitat area and quality have big-

ger effects than variations in spatial arrangement of habitats or properties of the intervening land.

Even if structural features in the matrix have a measurable effect on dispersal rates, this does not

necessarily lead to significant increases in population viability.

3. Large and high-quality habitats provide source populations and locations for colonisation, so

they are the main determinants of the capacity of species to shift their distributions in response to

climate change because populations must be established successively in each new region.

4. Synthesis and applications. Retaining as much high quality natural and semi-natural habitat as

possible should remain the key focus for conservation, especially during a period of climate change.Key-words: aggregation, climate change, conservation planning, corridor, landscape, matrix,

uncertainty

Introduction

Hodgson et al. (2009) noted that habitat area, quality, and

aggregation were key components of landscape-scale conserva-

tion, and that prioritising habitat area and quality would be a

robust way to facilitate connectivity and the persistence of bio-

diversity in the face of climate change. Doerr, Barrett & Doerr

(2011) suggest that structural features to facilitate dispersal in

non-breeding habitat are valuable targets in themselves, and

can be measured with certainty equal to that of area, quality,

and aggregation. They further suggest that we misunderstood

the term connectivity conservation. In this reply to the Forum

by Doerr, Barrett & Doerr in this issue, we begin by summaris-

ing where we are in agreement. We then present our case that

Doerr, Barrett & Doerr, in focussing narrowly on non-habitat

structural features, have ignored the bigger picture of relative

priorities for conservation under climate change.

Hodgson et al. (2009) and Doerr, Barrett & Doerr (2011)

present different ways of approaching the same overall goal;

limiting extinctions and maintaining functioning ecosystems.

Because of the complexities of ecology and human impacts in

different regions, no single prescription for conservation will

work everywhere. So, we agree with Doerr, Barrett & Doerr

(2011) that conservation strategies need to be tailored to the

landscape. We also fundamentally agree about which factors

affect the persistence of populations and metapopulations (Do-

err, Barrett & Doerrs Fig. 1 essentially expands our boxes for

dispersal mechanism and potential for barriers or conduits in

non habitat). However, we disagree about the relative impor-

tance of the various factors: habitat area, habitat quality, the

spatial arrangement of habitats (aggregations and connections)

and the properties of the intervening non-breeding (matrix)

land. Hence, we providehere evidence in support of our assess-

ment of the relative importance of these landscape attributes.

Relative importance of landscape attributes

H A B I T A T A R E A

Successful reproduction is confined to natural andsemi-natural habitats for the majority of terrestrial species.*Correspondence author. E-mail: [email protected]


2010 The Authors. Journal of Applied Ecology 2010 British Ecological Society


13/16

In the context of climate change, multi-generational range

shifts are facilitated initially by large habitat areas that

support large source populations, by substantial intervening

habitat areas to support breeding and generate propagules

en route, and by high habitat availability within target

regions to ensure eventual persistence (Table 1). Maximis-ing area is also likely to increase diversity via increased

habitat heterogeneity. Contrary to Doerr, Barrett & Doerr

(2011), we contend that there is generally a large amount

of natural or semi-natural habitat with insufficient protec-

tion. Tropical forest, for example, is converted to other

land uses at around 05% annually (FAO 2005). It is usu-

ally much more effective and cheaper to retain what is still

present than to attempt to recreate it.

H A B I T A T Q U A L I T Y

Quality improves persistence by increasing population

growth, resulting in larger propagule numbers, increased

likelihood of colonisation, and higher population growth

rates following colonisation. Many aspects of habitat qual-

ity are, as Doerr, Barrett & Doerr (2011) suggest, species-

specific and difficult to control. However, some aspects of

quality affect many species similarly, such as nutrient pol-

lution, the spread of invasive species or major habitat dis-

turbances. Much of the worlds biomes are now partly or

substantially altered by, for example, selective logging, par-

tial fertilisation of grasslands, drainage of wetlands, and

elimination of fire or large mammals. Preventing further

degradation and increasing the quality of already-degraded

areas can generate extremely large differences in populationdensities (e.g. Table 1) and, therefore, colonisation and

population growth, including range expansion.

S P A T I A L A R R A N G E M E N T O F H A B I T A T S

The locations of remaining habitat fragments in landscapes

are known to be important to long-term population persis-

tence (Hanski & Ovaskainen 2000), but the size of this effect

is smaller than the effects of quantity and quality (Table 1),

principally because the production of new individuals takes

place within habitats, regardless of their location (Ovaskai-

nen 2002). Habitat aggregation generally increases thechance of a propagule landing in suitable habitat, and there-

fore of a patch of habitat being colonisedoccupied, but it

can only compensate a little for deficiencies in quantity and

quality (Table 1). Under climate change, the benefit of aggre-

gation may be less certain because aggregating remaining

habitat within a few regions may leave dispersal barriers that

will eventually need to be bridged. When suitable habitat is a

very low proportion of the landscape, there may be a trade-

off between maximising aggregation and reducing the largest

dispersal barriers. There is evidence that corridors may

increase dispersal rates between patches to some extent

(Table 1), but an increase in dispersal per se is not direct evi-

dence of an increase in population viability.

N O N - B R E E D I N G H A B I T A T ( O R T H E M A T R I X )

Interventions in the matrix could contribute to population via-

bility by overcoming behavioural barriers to crossing certain

boundaries or land-cover types, or by reducing dispersal mor-

tality. Managing the matrix can result in modest increases indispersal between nearby habitat patches (by ca. 25%,

Table 1). However, we could find no robust evidence that

matrix condition alters long-distance, multi-generational range

changes. The likelihood of leaving an individuals natal habitat

patch may increase if the intervening matrix is favourable, but

movements typically become faster and straighter when an

individual is in a hostile matrix environment, and this leads to

much longer realised dispersal distances (Ovaskainen et al.

2008; Zheng, Pennanen & Ovaskainen 2009). The longest dis-

persal distances are the most important for maintaining genetic

diversity and for range expansions under climate change (Neu-

bert & Caswell 2000; Trakhtenbrot et al. 2005). We also note

that a whole different set of considerations apply to wind- and

water-dispersed species, and to the four kingdoms other than

animals. The suggestion of Doerr, Barrett & Doerr (2011) that

dispersal behaviour could be universal is centred on an exam-

ple that involved a small number of well-studied and related

species with high cognitive abilities.

Uncertainty and robustness

Doerr, Barrett & Doerr (2011) argue that structural connec-

tivity can be measured with reasonable certainty. The issue

to us is not the development of a repeatable metric, but

whether variation in such a metric is a good predictor ofmulti-generational range expansions for a wide range of

different taxa. The effect of the matrix on long-distance

dispersal and colonisation is virtually unknown; and we

already know that short-distance matrix effects are species

specific (Eycott et al. 2009; Prevedello & Vieira 2010). Doerr,

Barrett & Doerr (2011) reasonably counter that measure-

ment of habitat quality is an issue, and also species-specific,

but it is much easier to investigate, for example by relating

the population densities of individual species or broader

measures of diversity to environmental and biotic variables.

We strongly disagree with the Doerr, Barrett & Doerr (2011)

view of area, quality and connectivity that all provide the

same degree of conservation certainty because their benefits

depend on the interactions between them. It is clear to us

(e.g. Table 1) that different variables that interact in a given

model do not all have the same effect sizes or associated

uncertainties. Uncertainty about functional connectivity is

higher than any of the above-mentioned factors because it

adds uncertainty about dispersal distances and behaviour on

top of uncertainty about what constitutes habitat quality.

Crucially, though, this uncertainty does not negate the large

effects of habitat area and quality over large numbers of

species and landscapes, because only metapopulations close

to their extinction threshold are substantially limited by

connectivity (Hodgson et al. 2009: Fig. 1).

Area, quality and connectivity 149



14/16

Table 1. Brief overview of evidence for the importance of different landscape-scale factors in conservation. Priority has been given to review

papersand meta-analyses, papersthat compare more than one factor, andpapers that relatefactors specifically to range expansion

Landscape attribute Summary of evidence Sources

Habit at a rea Eas tern US tre es range exp ansi ons de pe nde nt on so urc e

populations

Iverson, Schwartz & Prasad

(2004)

Patch area has consistently bigger effect (up to 100 times

greater F ratio in ANOVA) than connectivity measures on

species richness and abundance of plants and butterflies in

fragmented grasslands in southern Germany

Bruckmann, Krauss &

Steffan-Dewenter (2010)

Plant and butterfly species richness of calcareous grasslands

in northern Germany is affected by patch area, and not

significantly by isolation or surrounding landscape

heterogeneity

Krauss, Steffan-Dewenter &

Tscharntke (2003);Krauss

et al. (2004)

Simulated and observed expansion rates of butterfly Pararge

aegeria >40% slower in landscape containing 24% less

woodland cover

Hill et al. (2001)

Hesperia comma butterfly range expansion rates in UK

strongly related to habitat quantity

Wilson, Davies & Thomas

(2010)

Habitat quality* Positive effects of quality on occupancy for plants, butterflies,

moths, other insects, amphibians, birds, small mammals,

primates and carnivores

Reviewed by Mortelliti, Amori

& Boitani (2010)

Correct vegetation management can increase butterfly

densities 10- to 100-fold

Thomas, Simcox & Hovestadt

(2010)

Macaw (Ara and Orthopsittaca spp) density in Amazon varies

>10-fold with respect to indicators of human disturbance

Karubian et al. (2005)

Sea otters (Enhydra lutris nereis) range expansion dependent

on population growth rate

Tinker, Doak & Estes (2008)

Quality the dominant factor affecting butterfly and moth

abundance and diversity in a Finnish landscape

Po yry et al. (2009)

Spatial pattern 1:

aggregation (aka spatial

autocorrelation)

Isolation negatively affects colonisation rate and occupancy Reviewed in Hanski (1999:

Chapter 9)

Negative effect of isolation on patch occupancy in three

English butterflies (effect of habitat quality is 23 times

larger).

Thomas et al. (2001)

Positive effects of aggregation on flower visitation and seed

set in pan-European study of 10 plant species (although

patch area effect is bigger)

Dauber et al. (2010)

Aggregation measures have positive effects on species richness

and abundance of butterflies (and to lesser extent plants) in

fragmented grasslands, though not as large as the effects of

area

Bruckmann, Krauss &

Steffan-Dewenter (2010)

Spatial pattern 2: habitat

connections (corridors

and stepping stones)

Average 16-fold increases in exchange rates between patches,

based on systematic review in which the corridor is the same

type of habitat as the connected patches

Eycott et al. (2009)

Modest positive effect of corridors on dispersal rate:

standardised effect size


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This leads to the issue of robustness. Understanding and

modelling the detailed behavioural responses of individuals to

multiple landscape elements is an interesting area of research.

However, if such details are to be incorporated within multi-

generational distribution models, we would argue that other

details (e.g. habitat changes, local adaptation, species interac-

tions, evolution of dispersal) are equally relevant, and that they

all have associated uncertainties. The robustness of such com-

plicated modelling will almost necessarily be low. The intention

of the original Hodgson et al. (2009) argument was to identify

robust, easy to understand and easy to implement conserva-

tion strategies.

What role for connectivity conservation?

It is possible that everybody understands connectivity con-servation to mean a holistic, landscape-to-continental scale

conservation method that accounts for all important factors

(including habitat quality, quantity, spatial habitat arrange-

ments, the character of the intervening landscape), and the

consequences of these for persistence and resilience of multi-

ple species, in a location-specific manner (Doerr, Barrett &

Doerr 2011). If so, our fears about an over-emphasis on con-

nectivity may be unfounded. But if connectivity conserva-

tion is all this, then the term is actually an unneeded alias

for biodiversity conservation. Such a re-branding may be

useful to stimulate investment in conservation, but we should

still be aware of the potential for confusion it creates. Ouroriginal concern was not that there were problems with every

activity labelled connectivity conservation, but that the

review of Heller & Zavaleta (2009) found that increasing

connectivity was the predominant proposed solution for

conservation under climate change.

We think that considerations of connectivity have an impor-

tant place in conservation planning (e.g. Moilanen et al. 2005;

Moilanen & Wintle 2007; Moilanen, Wilson & Possingham

2009; Carroll, Dunk & Moilanen 2010). Recent awareness of

connectivity has undoubtedly been helpful to conservation: it

has freed conservationists from focusing too narrowly on indi-

vidual protected areas, and has brought landscape-scale and

spatial considerations into conservation. But our concern was

how connectivity is often seen as the solution when the funda-

mental problem is an inadequate quantity of high-quality habi-

tats. It is fortunate that many of the existing connectivity

conservation programmes such as the Great Eastern Ranges

(GER) initiative are heavily focused on increasing and consoli-

dating natural habitat area (the first three of five GER goals;

Mackey, Watson & Worboys 2010). This serves to reinforce

the impression that connectivity conservation may be a new

name for the business of conservation that has long recognised

the role of habitat quantity, quality, and connectivity (e.g. Dia-

mond 1975).

Based on the weight of current evidence (Table 1) and our

original arguments (Hodgson et al. 2009), we remain of the

opinion that maintaining (and where feasible restoring) large

areas of environmentally diverse, high-quality (low human

impact) breeding habitats should be the primary focus of con-

servation when resources limit the range of conservationactions that can take place. Compared to this, structural fea-

tures of the matrix which are not breeding habitat for many or

any species are a minor consideration.

Acknowledgements

We thank Amy Eycott, Jeremy Thomas and Kevin Watts for providing mate-

rialpermission tocite work inpress.

References

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specialists suffer from reduced connectivity in fragmented landscapes. Jour-

nal of AppliedEcology, 47, 799809.

Carroll, C., Dunk, J.R. & Moilanen, A. (2010) Optimizing resiliency of reserve

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