Running Head: The Ecology of Information

THE ECOLOGY OF INFORMATION: AN OVERVIEW ON THE

ECOLOGICAL SIGNIFICANCE OF MAKING INFORMED DECISIONS

Kenneth A Schmidt1,*, Sasha R. X. Dall2, Jan A. van Gils3

1 Department of Biological Sciences, Texas Tech University, MS 3131, Lubbock, TX, 79424, USA

2 Center for Ecology & Conservation, School of Biosciences, University of Exeter, Tremough, Penryn,

TR10 9EZ, UK TR10 9EZ

3 Department of Marine Ecology (MEE), NIOZ Royal Netherlands Institute for Sea Research, P.O. Box

59, 1790 AB Den Burg, Texel, and Department of Plant-Animal Interactions (PAI), Centre for Limnology,

Netherlands Institute of Ecology (NIOO-KNAW), Rijksstraatweg 6, AC Nieuwersluis, The Netherlands

* Corresponding Author:

Kenneth Schmidt kenneth.schmidt@ttu.edu806-742-2723806-742-2693 FAX

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ABSTRACT

Information is characterized as the reduction of uncertainty and by a change in the state of a receiving

organism. Thus, organisms can acquire information about their environment (or future environment) that

reduces uncertainty and increases their likelihood of choosing a best-matching strategy. We define the

Ecology of Information as the study of how organisms acquire and use information in decision-making

and its significance for populations, communities, landscapes, and ecosystems. As a whole, it

encompasses the reception and processing of information, decision-making, and the ecological

consequences of making informed decisions. The first two stages constitute the domains of, e.g., sensory

ecology and behavioral ecology. The exploration of the consequences of information use at larger spatial

and temporal scales in ecology has generally lagged behind the success of these other disciplines. In our

overview we characterize information, review statistical decision theory as a quantitative framework to

analyze information and decision-making, and discuss some potential ecological ramifications. Rather

than attempt a superficial review of the enormity of the scope of information we highlight information use

in three areas: breeding habitat selection, interceptive eavesdropping and alarm calls, and information

webs. Through these topics we discuss specific examples of ecological information use and the emerging

ecological consequences. We emphasize recurring themes: information is collected fromthrough multiple

sources, over varying temporal and spatial scales, and in many cases links heterospecifics to one another.

This leads to questions where further development is needed: (1) how are information sources are

integrated and prioritized, (2) how does the spatial and temporal correlation between when and where

information is obtained and acted upon affect behavioral strategies, population processes, and ecological

interactions, (3) how best to integrate interaction webs and information webs between organisms.

Keywords: alarm calling, Bayesian updating, breeding habitat selection, eavesdropping, information,

predation risk, statistical decision theory

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INTRODUCTION

The Ecology of Information is the study of how organisms acquire and use information in decision-

making to manage their lives of, e.g., finding food, selecting habitats, avoiding predators, and allocating

effort to current and future reproductive success, and its significance for populations, communities,

landscapes, and ecosystems. It is a burgeoning and integrative field that melds together the various

disciplines that deal with the reception and processing of information on the one hand and the ecological

and evolutionary consequences of making informed decisions on the other hand (Fig. 1). Information is

considered one of the central biological concepts of the twentieth century (Maynard Smith 2000,

Jablonska 2002) and is critical to the adaptive process (Plotkin 1997, Dall et al. 2005). The concept of

information (or its various subdivisions) as related to the fields of animal behavior and ecology has been

reviewed at least six times since 2004 (Danchin et al. 2004, Dall et al. 2005, Vos et al. 2006, Seppänen et

al. 2007, Bonnie and Earley 2007, and Valone 2007), and as a more general concept in biology by

Maynard-Smith (2000) and Jablonka (2002).

This set of excellent review and synthesis papers has exposed the concept of information to many

ecologists, and has taken the first important step of presenting, defining, and circumscribing the role(s) of

information in ecology as well as illustrating a diverse set of ecological contexts and organisms that

utilize information. They have been extremely successful in this regard; however, the limits of a single

review article leaves little room for exploring ecological processes or the relevance of information for

processes and patterns within populations, communities, and ecosystems – i.e., the spatial and temporal

scales that form the bulk of the ecological studies (Fig. 1). Thus, with a strong backdrop of information

in ecology already in place, there still remains a very real and urgent need to bridge the gap between the

behavioral, ecological, and conservation sciences (Fryxell and Lundberg 1998, Sutherland and Norris

2002) with information at its core. By way of this overview, we hope to highlight some areas of

successful incorporation of information as well as areas where further development is needed. However,

the scope of information in evolution and ecology is enormous and cannot be covered in any reasonable

manner in a single paper (or indeed a featured set of papers); likewise, the upsurge of interest as catalyst

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for recent reviews means that a certain amount of redundancy is unavoidable. We have taken the strategy

of selecting a narrow set of topics to discuss the implications that are more relevant to populations,

communities, landscapes, and ecosystems that have not necessarily been the main subject material for

past reviews. But this also means we barely scratched the surface of the functional role of information in

ecology.

Characterizing information

An abstract property of events and entities that make their characteristics predictable to

individuals… [It] enables…individuals to make choices, select their activities …appropriately for

their needs and opportunities. (Smith 1977:193)

This passage of Smith (1977) expresses two elements that are typically used to characterize information:

(1) the reduction of uncertainty, i.e., information is that which makes the world more predictable

(syntactic view of information: Shannon and Weaver 1949, Danchin et al. 2004) and (2) change in the

state of a receiver in a functional way (semantic view: Blumstein and Bouskila 1996, Jablonka 2002; Dall

2005). Heterogeneity and variability limit an organism’s ability to possess complete knowledge of the

state of its current world or anticipate future conditions, and hence choose an appropriate strategy for the

actual set of conditions it will encounter. In the face of this uncertainty organisms can acquire

information about their physical and biotic environment (or future environment) that reduce uncertainty

and increase their likelihood of choosing a best-matching strategy. Implicit in this description is that for

information to exist and to have fitness consequences there must be both variation in environmental

conditions (e.g., states) and in phenotypic strategies (Stephens 1989). Moreover, it assumes organisms

make adaptive choices under the existence of constraints, a central premise of the field of behavioral

ecology (Mitchell and Valone 1990). While this last premise is demonstrably false in many cases, it is

often so because the genome or phenotypic plasticity fails to precisely track a changing environment (or

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correctly perceive a constant environment). Ecological traps and information disruption are two

anthropogenic causes for these events that we discuss throughout the paper.

Terminology: Box 1 provides a glossary for types of information discussed throughout that is

based on and expanded by Wagner and Danchin (this issue). Information can come from almost any

source: an organism’s abiotic environment (e.g., physical cues) biotic environment (e.g., signals and

biological cues from con- and heterospecifics), perception of its own internal state (e.g., hunger,

motivation), social learning, and trial and error experience. Furthermore, even when sources of

information are private, such as state or motivation, information can become public through indirect

means following the pathway described by Seppänen et al. (2007; Box 1). For example, Wong et al.

(2005) demonstrated that sand fiddler crabs (Uca pugilator) use observations of threat-induced responses

of neighbors (actions, stage 2 in Seppänen et al. 2007; Box 1) to guide their own refuge-seeking behavior.

Breeding birds may preferentially settle on territories where conspecific reproductive success

(consequences, stage 3 in Seppänen et al. 2007; Box 1) was high in prior years. Public information based

on the actions or consequences of other individuals (i.e., social information; Box 1) may be actively

sought out by both conspecifics and heterospecifics. It is possible that the quality of information degrades

through this sequence (Giraldeau et al. 2002, van Bergen et al. 2004, Seppänen et al. 2007).

Alternatively, observations of the primary observer’s actions and consequences may provide higher

quality information (i.e., more reliable cues) since the primary observer confronts ambiguity (e.g., errors

in signal detection; Bradbury and Vehrencamp 1998) or uncertainty (Stephens 1989), and its actions may

be influenced by gambles (e.g., risk-sensitive behavior; Stephens and Krebs 1973) or seeking insurances

(Dall and Johnstone 2002) that secondary observers may wish to avoid.

Lastly, it is important to distinguish between the source of information and its content; our

terminology refers only to the former. It is entirely possible that a source of information that is social in

origin (e.g. the feeding performance of flockmates) can inform about non-social issues (e.g. the amount of

food in the environment). Identifying sources is important as, e.g., social information has unique

implications for ecology and evolution, such as cultural evolution (Danchin et al. 2004) or information

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webs and the consequences of their deterioration (Vos et al. 2006, Holt 2007; Seppänen et al. this issue;

see Concluding Discussion). However, in other contexts the type of information can be safely ignored

relative to its content. In the later sections that discuss ecological processes we often do just that: focus

more on the content than the source of information.

Information, uncertainty, and phenotypic variation: Phenotypic variation is an outgrowth of

spatiotemporal variation in the environment and its predictability, i.e., information (Levins 1968,

Donaldson-Matasci et al. 2008, Lachman et al. this issue). This is especially true of phenotypic plasticity;

however the genome itself is a record of the past success of heritable strategies. Thus phenotypic

variation is influenced by (1) past information stored in the form of allelic (genetic) variation (2)

maternally-acquired cues (Massot and Clobert 2000, Mathis et al. 2008) capable of producing epigenetic

effects in one or more future generations (Gilbert and Epel 2008), and (3) current signals or cues that

produced variation through norm of reaction, polyphenism, or behavioral plasticity. A discussion of the

evolution of plasticity (and the related concept of bet-hedging as a response to uncertainty) would go far

beyond our overview. But we note that the form of plasticity will be influenced, in part, by the degree to

which the environment varies (spatiotemporal correlation) and the relative cost of incorrectly matching

your strategy to the environment. If change is slow (e.g., ponds tend be fishless or not during a

cladoceran’s lifetime) then irreversible developmental shifts (protective crest development) may be

favored over a sophisticated perceptual system that is costly to maintain. On the other hand, behavioral

flexibility may be favored if changes are rapid and frequent within an individual’s lifetime, e.g., nest

defense or broken wing display in response to predators that frequently move in and out of the vicinity of

a plover’s nest. We largely restrict our overview to behavioral plasticity. Behavior has attracted far

greater attention from the field of statistical decision theory (next section), and is perceived as a more

important proximate causal agent of higher level ecological processes. However, this perception may be

more of a statement about how the field of biology is fractionalized.

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Statistical decision theory - In their review, Dall et al. (2005) promote statistical decision theory (SDT)

as a quantitative framework from which to analyze the use of information by organisms (also see

McNamara and Houston 1980, McNamara et al. 2006, and Oikos v.112, issue 2). At its heart is the use of

Bayesian methods (specifically Bayes’ theorem for calculating conditional probabilities) to explore how

organisms integrate prior expectations based on personal experience and evolutionary history (i.e., genetic

information) with new information to arrive at a revised, posterior expectation. Take the example of mate

choice: choosy females are assumed to have (perfect) knowledge of the distribution of male quality (e.g.,

parenting skills, parasite loads) in a population, whereas the quality of an individual male is uncertain and

must be sampled through observation of song, display, etc. (Getty 1996, Luttbeg 1996). The value of

sampling information lies in the formation of a revised posterior expectation of the individual male’s

quality that reflects reduced uncertainty associated with possible outcomes (Dall et al. 2005). We direct

our readers to reviews on the SDT framework (Dall et al. 2005) and empirical studies of Bayesian

behavior (Valone 2006; half the issue is in fact devoted to Bayesian foraging) for recent updates in this

field and it’s important to the ecology of information. We make reference to SDT throughout, but for

brevity we do not duplicate the material in these reviews.

Two salient questions not directly addressed in the reviews are: (1) what is the relationship

between information updating and information use and (2) how do alternatives to Bayesian updating

compare? To address the former, it has been suggested (to us) that SDT tackles only the question of how

information is updated and not how it is used (and thus its relevance for ecological processes). This may

be a reaction to how SDT has been used in the past, for the statement is certainly not true. For example,

van Gils (this issue) demonstrates that the Bayesian Potential Value Rule (Olsson and Brown 1996)

predicts the pattern of area-restricted search when foraging in a spatially correlated environment. For the

first time, we have a realistic theoretical representation of this behavior. Schmidt and Whelan (this issue)

used SDT to predict optimal renesting behavior in single-brooded birds. One prediction of their model

they called the Renester’s Paradox: habitats with greater nest failure that require more nest attempts, on

average, to successfully raise a brood are the very same that are selected for fewer nests attempted.

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Furthermore, they show how uncertainty surrounding habitat quality and the process of information

updating links changes in the quality or proportion of one habitat type to behavior in the other habitat.

Kokko and Sutherland (2001) modeled breeding habitat selection combined with habitat

degradation without changing preferences (i.e., an ecological trap scenario). Notably, they demonstrated

that variation in how priors are governed can greatly alter the threat of extinction and place very different

demands on management or intervention. Their model incorporated rules-of-thumb (e.g., imprinting or

learned preferences) rather than take an explicit Bayesian approach. Behavioral rules may be common

(McNamara and Houston 1980, Bouskila and Blumstein 1992; see next section), and often perform close

to optimal Bayesian solutions when the two have been compared (e.g., Beauchamp 2000, Welton et al.

2003). However, this may not be true when the circumstances under which the rule evolved have

changed thus generating evolutionary traps (Schlaepfer et al. 2002; and see Conservation biology and

ecological traps).

There is little doubt that SDT (especially Bayesian approaches) need to be expanded beyond a

handful of contexts. To date, Bayesian methods have mostly found their way in “simple” short-term tasks

such as foraging or predation-avoidance (e.g., Rodríguez-Gironés and Vásquez 1997, Olsson and

Holmgren 2000, van Gils et al. 2003). But even here one may ask to what extent do solutions to problems

such as patch departure rules influence populations, communities, landscapes, and ecosystems? Olsson

and Brown (this issue) give us glimpse into the future by examining how information states (e.g.,

Bayesian vs. fixed-time foragers) sculpt the resource distribution in their environment in ways that may

promote or prevent species coexistence. Following Olsson and Brown’s lead in incorporating Bayesian

approaches and behavioral strategies in population and community models (e.g., Fryxell and Lundberg

1998, Sutherland and Norris 2002) will begin to close the gap between information updating and

ecological processes at higher scales.

From information to an Ecology of Information – That information use can have significant population

consequences is demonstrated in this section using a quintessential ecological question: population

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persistence and the distribution and abundance of individuals (we focus only on persistence here). We

start with a model of metapopulation persistence in anwithin information-free world (Bascompte et al.

2004). We do not fault the authors for this; rather they developed an elegant and useful model to

illustrate the relationship between the persistence of a stochastic patchy population network and the

number of habitat patches connected through dispersal. Under the assumptions 1) that patches experience

periods of density independent population growth ( > 1; good years) or decline ( < 1; bad years) with

equal probability, 2) patches are decoupled with respect to temporal variability (i.e., good and bad years

are assigned to patches independently), and 3) patches are spatially coupled through even dispersal

events, the geometric growth rate of a population network, GEOM, composed of n patches can be

approximated as the spatial-arithmetic mean growth rate, ARITH, minus a sampling error for small n. If for

any habit patch good and bad years are equally likely and uncorrelated there is no information available to

choose a patch. However, if patch quality is temporally correlated (regardless if good and bad years

remain equally likely in the long term) then previous experience informs an individual of the likelihood

the current conditions will persist. Correlation makes information available; however the organism still

requires the means of detecting, processing, and using the information. Thus, even in a temporally

correlated world even dispersal is uninformed behavior. The result is that regardless of the number of

patches (or the presence of temporal correlation), GEOM will never exceed ARITH such that if ARITH < 1.0

the metapopulation quickly becomes extinct (Fig. 2). An alternative is to adjust patch fidelity based on

prior experience: return to (or stay at) patches that experienced high productivity the prior year and vacate

patches that had poor productivity the prior year. This win-stay:lose-switch (WSLS) rule performs no

better than even dispersal in a world lacking temporal correlation and soin which prior experience is not

informative. However, the combination of the WSLS rule and temporal correlation (experience is

informative) has dramatic consequences on the persistence time of the metapopulation (Schmidt 2004;

Fig. 2). While we detail this single example, other excellent studies drive home the point that models of

ecological processes built around partiallyimperfectly informed organisms often behave dramatically

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different from information-free or perfect information scenarios (e.g., Brown et al. 1999, Vos et al. 2001,

Donahue 2006), neither of which is realistic or likely to be common.

INFORMATION AND ECOLOGICAL PROCESSES

In this section we expand on information use in three areas: (1) Ecological developmental biology briefly

considers environmental cues that direct phenotypic variation in morphology and physiology, (2)

Breeding habitat selection, which makes use of multiple sources of information collected over varying

temporal and spatial scales, and (3) Alarm calling and heterospecific information transfer within a

landscape context.

Ecological developmental biology – Some decisions in an organism’s life are made only once and are

irreversible. These include selecting among alternative developmental endpoints (polyphenism) and life-

cycle progressions timing (e.g., diapause, metamorphosis) that directly or indirectly affect morphology

and physiology in addition to behavior. These decisions are guided in part by environment cues (e.g.,

photoperiod, temperature, nutrition, predation risk, social proximity) and concern the emerging field of

ecological developmental biology (Gilbert 2001, Gilbert and Epel 2009). Examples include predator-

induced shell morphology in the barnacle Thais lamellosa (Palmer 1985), nutrition-induced polyphenism

in Nemoria arizonaria caterpillars that develop a cuticle resembling either an oak catkin or oak twig

depending on the season in which they hatch (Greene 1989), and vibrational assessment of predation risk

and premature hatching in embryo red-eyed tree frogs, Agalychnis callidryas (Warkentin et al. 2007); for

many other examples see reviews in (Pechenik et al. 1998, Gilbert 2001, Relyea 2007).

From an information perspective there may be little fundamental difference between these single,

irreversible decisions and rapidly repeatable and reversible behavioral decisions: the framework of SDT

can apply to either. For instance, Warkentin et al. (2007) couched their study of premature hatching in

red-eyed tree frogs as a signal detection problem: balancing the costs to frog embryos of missed cues

(snake predation on embryos) and false alarms (greater susceptibility of premature hatchlings to aquatic

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predators. At the same time, developmental decisions have somewhat unique circumstances. In many

cases there is no direct assessment of the future environment (e.g., aquatic ↔ terrestrial) and thus limited

opportunity for learning. On the ecological side, there may be large latent effects stemming from

choosing an alternative fixed phenotype or altering developmental timing (Pechenik 2006). These effects

may capable of producing large population and community consequences. Lastly, global climate change

and other anthropogenic effects are rapidly altering the probabilistic linkagesconditional probabilities

between (future) state and proximate cue, and the reliability of chemical cues, which often direct

development progression, is being disrupted by anthropogenic substances.

Breeding habitat selection -Spatial heterogeneity and temporal variability in the underlying factors that

contribute to breeding productivity (e.g., food abundance, predation risk) are widespread (e.g., Lewis &

Murray 1993, Schmidt et al. 2006, Simpson et al. 2008). Choice of breeding location has high fitness

consequences, and it is not surprising that organisms acquire information to guide their decisions.

Although selecting a breeding location within a hierarchy of landscapes, habitats, territories, and breeding

sites (e.g., nest sites, dens) differs considerably among taxa, broadly speaking the potential sources of

information and their use are likely to generalize (Box 2). For instance, social information, based on

presence (conspecific attraction; Stamps 1988, Fletcher 2006) or performance (habitat copying; Clobert et

al. 2001) may be advantageous because they are integrative measures, provide greater sampling power

(i.e., more independent sources), and, in the case of post-reproductive cues may reveal the consequences

of conspecifics’ decisions. Thus, prospecting (i.e., gathering local information on, e.g., reproductive

success; Reed et al. 1999, Ward 2005) is likely to be an important behavioral strategy that is implemented

throughout the year or at least those critical periods when information is least costly and most readily

available. Recent reviews have highlighted the apparent ubiquity of prospecting in birds where it has

been best studied (Reed et al. 1999). Among vertebrates, studies have shown they use conspecifics

presence, density (Cote and Clobert 2007), and reproductive productivity or its correlates (e.g., post-

breeding singing rates, Betts et al. 2008; quality/quantity of fledglings produced, Doligez et al. 2002,

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Parejo et a. 2007) when choosing breeding sites or to find suitable habitat using phonotoaxis and

orientation (Diego-Rassila 2004). These cues may provide high quality information on habitat or site

quality and may be used to reduce search and settlement costs (Stamps 2001, Fletcher 2006). In addition,

proximate cues, e.g., presence versus density, may provide unique or complementary information on

different components of habitat (e.g., suitability versus intraspecific competition). Moreover, these

strategies are not limited to cues from conspecifics; cues from heterospecifics may also be used for these

same or alternative types of information or as cost saving strategies (Mönkkönen and Forsman 2002,

Diego-Rassila et al. 2004, Seppänen et al. 2007). Prospecting may also include assessment of habitat

components, such as predator activity and food availability, and breeders may eavesdrop on inadvertent

public cues, such as vocalizations of predators (Emmering and Schmidt in review) prey, (Simpson et al.

2008), or competitors (Fletcher 2008).

Adaptive information use depends on the level of spatial and temporal correlation which places

bounds on the quality or amountreliability of information available (Doligez et al. 2003, Schmidt 2004,

Donahue 2006; see Box 2). High quality information sources will vary widely with spatiotemporal

correlation relative to the timing of prospecting and constraints that limit it. For example, in the kittiwake

(Rissa tridactyla) Boulinier et al. (1996) observed a ~30 day window over which the proportion of

successful nests at a given date reflects the productivity of a breeding patch, and a peak in the number of

prospectors in this window. Betts et al. (2008) provide example of a window of opportunity, but with

declining reliability over time, to use post-breeding singing as a cue to reproductive productivity (also see

Fletcher and Miller (2008) for timing of social information in the cactus bug (Chelinidea vittiger)).

Further documentation of these relationships is important because it establishes the relationship between

cue and consequence, quantifies a level of cue reliability, and may document the existence of spatial and

temporal constraints on prospecting and information use.

The multitude of putative information sources within and among perceptual modalities (visual

auditory, chemical), ecologies (hetero- and conspecifics), spatial (personal versus public) and temporal

(prior and versus current) domains presents ecologists with challenges and opportunities. How are these

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inputs combined? Are they redundant, complementary, or reinforcing? If data from two or more sources

contradict, which should take priority to maximize information acquisition? Only a handful of empirical

studies have examined how multiple measures of breeding success combine. In both kittiwakes (Danchin

et al. 1998) and collared flycatchers (Ficedula albicollis; Doligez et al. 2002) individuals differ in their

relative use of personal and patch (social) breeding success, revealing contextual sources of information

(prior success, age, sex difference) or possibly phenotypic differences among individuals (e.g., behavioral

syndromes). More such studies are desperately needed as well as experimental manipulations designed to

produce conflicting information as have been applied to foraging contexts (Kendal et al. 2004, van

Bergen et al. 2004, Coolen et al. 2005). In concert with this, we need further theoretical development that

incorporates the multitude of putative information sources seen in empirical studies, and under varying

scenarios of spatial and temporal predictability.

Ecological implications: population dynamics: Personal or public information on breeding

productivity may provide the information that leads to site dependent (SD) regulation, a potentially

widespread form of density dependence produced by the pattern in site (e.g., territory) settlement in

spatially heterogeneous environments (Pulliam and Danielson 1991, Rodenhouse et al.1997).

Information from prior success (WSLS-rule) can lead to prolonged persistence of metapopulations within

patchy landscapes (Fig. 2), whereas information from social cues (e.g., conspecific attraction) can deter

dispersal to new, high quality habitats (Ray et al. 1991, Forbes and Kaiser 1994). Nonetheless, SD

models assume perfect information and are phenomenological, whereas the WSLS-rule assumes prior

success trumps all other sources of information and is applied absolutely. A more reasonable alternative

is to make the WSLS rule probabilistic and conditional on context and other sources of information (e.g.,

Boulinier et al. 2008). Site dependent models, on the other hand, should become more mechanistic – in

the absence of mechanism they have no connection to the proximate source of information or its

spatiotemporal context, which limits their predictive power and insight into changing environments

(Sutherland and Norris 2002) or conservation strategies. For instance, understanding of whether a target

species uses information from con- or heterospecifics and the cues they use could benefit restoration of

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locally extinct populations and suggest strategies (e.g., staggered release over several years) and numbers

of animals for reintroduction (Mihoub et al. 2009).

Community ecology: Species differences in the acquisition or use of information is evident when

comparing the few studies that have examined simultaneous responses of multiple species to manipulated

information pertinent to breeding habitat (or site) selection indicate (Nocera et al. 2006, Emmering and

Schmidt in review; also a comparison of Parejo et al. 2007 and Doligez et al. 2002). Likewise, the

identical cue may vary among species in its reliability, i.e., ability to forecast future reproductive success,

due to the interspecific variation in spatiotemporal correlation (Parejo et al. 2005, Schmidt et al. 2006).

Informed individuals have greater fitness than uninformed (see papers in this feature by van Gils, Olsson

and Brown, and McNamara and Dall), hence those species better at assessing information or whose

fitness is more closely linked to temporally and spatially correlated environmental parameters may (1)

have a competitive advantage (Olsson and Brown, this issue), (2) ameliorate rapid ecological change, but

also (3) be more susceptible to ecological traps (Nocera et al. 2006). Broadening the ecological context

beyond breeding habitat selection, acquiring information may tradeoff with other fitness enhancing

activities (e.g., Dukas 2002, Schmidt et al. 2008) and could lead to mechanisms of coexistence (Olsson

and Brown, this issue). Coexistence or competitive displacement mediated through information may

complement purely performance-based mechanisms (e.g., Vincent et al. 1996), and are ripe for ecological

investigation. Lastly, heterospecific ‘informants’ may play a role in community assembly (e.g., Elmberg

et al. 1997, Mönkkönen et al. 1990, Fletcher 2008) when their presence provides performance or

productivity-based information to other species. Migrants may especially rely on the presence of

residents to gauge habitat quality (Mönkkönen and Forsman 2002, Thomson et al. 2003, Forsman et al.

2008), and as shown by Fletcher (2008) experimental vocal cues alone were sufficient to generate

differences in community structure.

Conservation biology and ecological traps: Ecological traps are defined as the result of

anthropogenic processes that decouple a formerly reliable cue from habitat quality resulting in

maladaptive habitat choice (Schlaepfer et al. 2002, Robertson and Hutto 2006). For instance, by

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orientating toward polarized light, odonates mistake asphalt surfaces, a cue ‘mimic’, for ponds and lay

their eggs on an unsuitable surface (Kriska et al. 1998). Statistical decision theory (Bradbury and

Vehrencamp 1998) provides a useful framework for examining an organism’s decision after receiving a

cue (or signal) based on (1) the correlation between cue and state (2) the fitness consequences of its

decision in those states (i.e., value of information), and (3) the commonness of the states (in Bayesian

terms, the animal’s prior). Under these considerations, an organism has an optimal cutoff probability

(i.e., minimizes the ratio of errors to correct choices weighed by their fitness value) that favors alternative

actions (select habitat A or B) on opposite sides of the cutoff. SDT has not been used in the context of

examining ecological traps, perhaps because it oversimplifies habitat selection, e.g., ignoring density

dependence. But SDT may be valuable because it illustrates unique pathways to a trap (1- 3 above).

Alternatively, adaptive behavior (the organism’s cutoff is optimal given the information available) can

lead to an increase in the proportion of individuals settling in the poorer habitat under any of the three

paths. But without an understanding of the decision process these would be incorrectly labeled as

ecological traps. Moreover, we do not expect to see an evolutionary response and conservation

management may be required.

Organisms may alternatively based habitat choice or settlement on behavioral rules-of-thumb

where priors, for instance, are based on learning. These rules may be more flexible and result in fewer

incorrect settlement decisions as shown by a theoretical analysis of Kokko and Sutherland (2001). When

priors were based on natal imprinting (being born is informative - philopatric preference strategy in

Kokko and Sutherland 2001) or the WSLS rule (learned preference strategy in Kokko and Sutherland

2001), individuals adjusted their habitat preferences to reduce the impact of ecological traps (modeled as

reduced quality of preferred habitat). Habitat preferences changed most rapidly under imprinting, but the

rate of preference change under WSLS still out paced the change of genetically fixed habitat preferences

when genetic variation was low. These analyses suggest that if cues are learned, then even if the

reliability of a cue is compromised organisms may rapidly readjust their cutoff threshold (Kokko and

Sutherland 2001), whereas if the cue use has a strong genetic component (Kriska et al. 1998) traps may

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persist. It is interesting that the WSLS rule may create a trap when changes in the reliability of cues

occurs (WSLS base on qualitative nest success; Schmidt 2001), but also rescue a population when traps

were created through a decrease in the quality of preferred habitat (Kokko and Sutherland 2001). The

lessons here are (1) depending on the ecological context the use of cues may both initiate and rescue a

population from an ecological trap and (2) how priors are formed can be the difference between requiring

management to save population or not.

Alarm calling in a community and landscape context – Alarm signals are a ubiquitous, largely public

strategy of informing others (intentionally or as a by-product) of dangers (most often predation risk) in

the environment (reviewed in Caro 2005). Regardless of how the interaction is characterized (i.e.,

altruistic or selfish), signals that carry information about danger or predator presence confer an advantage

to potential prey within perceptual range. We focus on heterospecific receivers and consider two

ecological implications: First eavesdropping on alarm calls to manage activity in time and space and

avoid predators may be common and of significant value (survival and foraging efficiency). Short-term

benefits include reacting with an appropriate anti-predator behavior and adjusting time allocation to

scanning for predators or to safer activities. It is difficult to extrapolate ecological consequences from

short-term benefits, so we consider the topic from the perspective of the presence of heterospecific alarm

callers. Second, the presence some …..of alter landscape connectivity and the resistance of habitat

elements (e.g., habitat edges) to facilitate movement through and within landscapes.

Alarm calls, eavesdropping, and predation risk: Birds in the Family Paridae (Parus, Baeolophus,

Poecile) are known to have high vigilance, aggressive mobbing behavior, and a sophisticated alarm

communication (Templeton et al. 2005) that extends to a large heterospecific audience (Langham et al.

2006). In the presence of black-capped chickadees (Poecile atricapilla), downy woodpeckers (Picoides

pubescens) decrease vigilance by 70% thereby increasing foraging rates (Sullivan 1984; also see Telleria

et al. 2001 for similar patterns among blue and great tits). Likewise, white-breasted nuthatches (Sitta

carolinensis) visit food patches more frequently in the presence of titmice (Dolby and Grubb 2000).

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Quantifying long-term advantages are difficult and far less common, but potentially far-reaching. For

example, Dolby and Grubb (1998) demonstrated long-term consequences for nuthatches occupying forest

fragments in which parids were removed for the winter, i.e., the time of year when they lead mixed-

species flocks. Both energetic state and survivorship declined (all mortality events were in parid-removal

fragments), although mortality events were rare and the difference was not significant. A similar

exclusion experiment, but during the breeding season, by Forsman et al. (2002) demonstrated decreased

reproductive productivity in pied flycatchers (Ficedula hypoleuca) in the absence of parids. These studies

minimally demonstrate that there is an effect of the presence of informants that has fitness consequences,

ostensibly through the production of alarm calls. However, it may be more likely that it is that the

absence of alarm signals and presence of non-alarm vocalizations that indicates safety (e.g., Sullivan

1984, Moller 1992), thereby reducing stress, increasing foraging efficiency, and avoiding unnecessary

activity and energetic expenditure (Vitousek et al. 2007). The latest study by Hetrick et al. (this issue-a)

found that changes in the performance and structure of alarm calls in the Eastern Tufted Titmouse (which

reference predator type and magnitude of risk; also see Templeton et al. 2005) are mirrored by changes in

contact calls. This suggests that alarm calls themselves are not necessary to communicate perceived

predation risk. Certainly more research is needed to determine how fitness benefits arise in these species.

Predation, information, and landscape connectivity: As the preceding section suggests,

perception of predation risk is modified by the availability of information, such as publicly broadcast

alarm signals or contact calls (and also other behavioral acts such as looking upward or fleeing or moving

toward cover; e.g., Wong et al. 2005). It stands to reason that this information combines with the physical

environment, perceptual aptitudes of the organism, and the costs and benefits associated with decision-

making to influence (facilitate or impede) movement among resource or habitat patches (Taylor et al.

1993); that is, to influence the functional connectivity of landscapes (Lima and Zollner 1996, Bélisle

2005). Information may influence the resistance of some organisms to cross patches boundaries

(Desrochers and Fortin 2000, Sieving et al. 2004, Tubelis et al. 2006) and habitat gaps (Bélisle and

Desrochers 2002), variation that has been linked to patterns of extinction in birds (Moore et al. 2008).

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Sieving et al. (2004) observed greater frequency of boundary patch crossings among songbirds when in

the presence of titmice. Tubelis et al. (2006) observed greater use of adjacent savannah habitat by mixed-

species flocks that form around sentinel species in relation to the level of predation risk (Ragusa-Netto

2002). Lastly, Wolters and Zuberbühler (2003) observed greater travel and broadening of niche space

(increased use of mid-canopy layer) in associating Campbell’s and Diana monkeys relative to isolated

species groups. These studies suggest the presence or absence of risk-base information may be akin to

landscape models that vary the quality of the matrix (e.g., Fahrig 2007). The effects may be especially

important in selecting migratory stopover sites (Nocera et al. 2008) where, because of lack of experience,

organisms are more vulnerable and less accurate at estimating predation risk (Pomeroy 2006, Pomeroy et

al. 2006, van den Hout et al. 2008).

As a consequence of the value of social information regarding predation risk, interspecific

sociality – from ‘loose’ attraction among heterospecifics to stable polyspecific associations - may be

attributed as much to the value of informants as to other ecological variables (Terborgh 1990, Goodale

and Kotagama 2005); however, demonstrating an effect of information per se, rather than simply selfish

herd, confusion, or dilution effects is difficult. Nonetheless, mixed-species groups of (most notably) birds

and monkeys form around specific nuclear sentinel species that signal a predator’s presence more often

and more reliably than others (Gaddis 1983, Bshary and Noë 1997, Goodale and Kotagama 2005)

suggesting that non-informational effects are insufficient to explain the phenomena (Wolters and

Zuberbühler 2003). Within these mixed-species groups, the risk-based information from sentinel species

extends to wider audiences (Goodale and Kotagama 2005, Langham et al. 2007) and leads to fitness

consequences (Dolby and Grubb 1998, Forsman et al. 2002) prompting their recognition as keystone

signalers (Hetrick et al. this issue-b). Moreover, an exchange of risk-based information in these systems

may represent an example of a stable resource exchange mutualism between species (Schwartz and

Hoeksema 1998).

CONCLUDING DISCUSSION

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In this section we break away from featuring specific ecological contexts to discuss some implications of

information at larger ecological scales and as a central organizing principle. Because little research has

been conducted at these levels to date our discussion is necessarily brief and more conjectural.

Nonetheless, in advancing our case we highlight the need to understand the possible consequences of

information at these scales.

Information Webs: Breeding habitat selection and alarm calling are themes of the larger

phenomena of using proximate cues or alternative sources of information to locate areas of high resource

abundance and low mortality risk; decisions which often dominate the daily lives of individuals and the

ecological interactions among organisms (Stephens et al. 2007). The responses affect the strength of

species interactions (Vos et al. 2006), generate non-lethal effects of predation (Brown et al. 1999), and

when cues are from heterospecifics, generate trait-mediated indirect interactions (Peacor 2003). It should

be evident therefore that there exists an information web that complements and greatly increases the

complexity of food webs and interaction webs (Dicke and Vet 1999, Vos et al. 2006, Holt 2007). Of what

consequence then is this information for food or interaction webs, i.e., beyond an individuals’ (or

strategy’s) own fitness? Predator-prey models suggest that adaptive behavior tends to destabilize

predator-prey dynamics (i.e., simple food-web modules) unless it is based on imperfect information

(Brown et al. 1999, Luttbeg and Schmitz 2000). Of what consequence is food web structure for

information? We are not aware that this question has been properly framed before. Vos et al.’s (2001)

work on infochemical mimicry (increasing noise) and confusion effects in tri-trophic interactions shows

that information can be a decreasing function of species diversity, specifically host specialization. In high

diversity systems infochemicals produced from herbivore-damaged leaves attracted parasitoids to plants

containing many individuals of non-host species. In theoretical analyses, effects in high diversity systems

weaken species interactions and lead to stabilized dynamics at intermediate species richness (Vos et al.

2001). Hence, community structure affects information that feedbacks to lower diversity.

Information as a third niche axis: We contend that information share center stage with abiotic

conditions and biotic resources as a third set of niche axes. To take an example, sunlight is an abiotic

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factor that is converted through photosynthesis and metabolic processes into a biotic resource for

heterotrophs. Sunlight also produces warmth and light (by definition) for activities such as foraging.

However, imagine a world where the daily mean number of hours of sunlight was equivalent to Earth’s

but randomly distributed throughout the year. Outside of H2S reduction as a source of energy, would life

even be possible? Perhaps, we but suggest it is the pattern (information) of sunlight in the form of

circadian rhythm that makes ecological systems what they are today. In a recent review, Resco et al.

(2009) discuss the ecological implications of plants’ ability to tell time noting that “[T]he circadian clock

affects gas exchange by ‘anticipating’ cycles of dawn and dusk” (Resco et al. 2009: 4; the anticipation

hypothesis). For instance, mutant, arrhythmic Arabidopsis show a 40% decrease in net carbon fixation

compared to wild-type (Dodd et al. 2005). Depending on the organism, sunlight is a consumable resource

or an abiotic condition; circadian rhythm is information.

Circadian rhythm of sunlight presents an extreme example, so consider something more mundane

but still exciting to most ecologists: species interactions. Predators kill or exert non-lethal effects such as

fear on their prey, but predators may also produce inadvertent social cues to their location in time and

space (i.e., information). Such information can enable prey to find spatial or temporal refugia from

predators; it is no wonder that predators (and prey) may behave with ‘purposeful unpredictability’ (sensu

Roth and Lima 2007; also see Gripenberg et al. 2007). Within the framework of consumer-resource

interactions, prey that acquire information to use to avoid predation can sustain zero-net population

growth at a higher density of predators, i.e., higher P* (Holt 1994). This in turn increases predators’ R*

(minimum prey abundance to achieve zero-net population growth) since informed prey are more difficult

to capture (Brown et al. 1999). The process can also start the other way around: information about prey

lowers a predator’s R*. If any of these feedback loops lowers, say the predator’s population density,

there may be reduced value to acquire information by the prey and their vulnerability goes up. The idea

that limiting factors (R* and P*, resources and predator, respectively) influence coexistence places

information as a critical element influencing community structure through population processes such as

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competitive exclusion (Tilman 1980, Holt et al. 1994); a process itself considered as a fundamental

property of the ecological niche (Leibold 1995).

Information as an Ecosystem Process: In the preceding section we pointed out that arrhythmic

Arabidopsis shows a decrease in net carbon fixation. Resco et al. (2009) would have us scale up these

effects suggesting that the circadian clock in plants drives gas exchange at the level of biosphere-

atmosphere interactions. If we accept this premise, if only to explore the consequences, then (1) Vos et

al. (2001) demonstrates that information can drive (in non-linear fashion) diversity and (2) Resco et al.

(2009) suggests information can drive ecosystem process. The point we wish to make is that ecologists

currently take a fairly rigid casual interpretation of ecosystem process-diversity relationships: diversity

drives the former. Yet these ignore the potential role of information as direct and indirect (e.g.,

information diversity ecosystem process) driver.

Noise and Info-disruption: Modern anthropogenic processes are greatly accelerating the loss of

species richness and diversity (Pimm et al. 2006, Bradshaw et al. 2009). Less appreciated is the loss of

information, including information processing (i.e., disruption) and transmission (e.g., low urban signal-

to-noise ratios; Rabin et al. 2006, Slabbekoorn and Ripmeester 2008). For example, info-disruption

(Lürling and Scheffer 2007) is the disturbance to chemical information transfer caused by pollutants, such

as heavy metals, surfactants, and pesticides. [Info-disruption is analogous to endocrine-disruption, which

itself is essentially a signal detection problem at the level of chemical recognition]. In aquatic systems

these substances are known to negatively affect anti-predator responses to chemical alarm signals in fish

(impaired avoidance), algae (reduced protective colony formation), and cladocerans (inhibited protective

crest development); see Lürling and Scheffer (2007). The noise associated with wind turbines interferes

with acoustic alarm calls among California ground squirrels (Spermophilus beecheyi) and subsequently

affects vigilance patterns and flight to burrow behavior (Rabin et al. 2006). Urban noise similarly affects

song (signal) efficiency in birds in turn affecting foraging-vigilance tradeoffs (Quinn et al. 2006) as well

as lowered abundance and reproductive success near highways (Slabbekoorn and Ripmeester 2008).

Species that communicate at frequencies above urban noise are little affected, and may come to dominate

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urban communities leading to faunal homogenization (Slabbekoorn and Ripmeester 2008). Invasive

species can also alter information flows, such as in the acoustic-orienting parasitoid fly (Ormia ochracea)

selecting for a song-less morph of the field cricket (Teleogryllus oceanicus); see Zuk et al. (2006).

Lastly, phenological mismatching due to global climate change is a consequence of information

disruption that has received considerable attention (e.g., Both et al. 2009, Brooks 2009). Mismatching

occurs when the timing of developmental or behavioral processes, such as hibernation, migration, or

reproduction, is altered triggered directly (temperature) or indirect from climatic cues (e.g., flowering

phenology)

Examples such as these are unfortunately too common, and the prospect of deteriorating

information webs led Holt (2007) to ask whether this was the “next depressing frontier in conservation?”

The sum of these effects can be large indeed and need prompt attention by conservation biologists. Not

just for conserving species but also the preservation of animal cultures (Laiolo and Tella 2007). We

recognize the value of genetic information by preserving genomes; it is time now to expand this

conservation priority to non-genetic biological information.

Conclusions: With one or more major reviews published each year since 2000 (see Introduction) one

may ask whether information is a passing fad or a general theme (we’re not arguing the only theme)

around which to organize empirical and theoretical research and conservation priorities in ecology and

evolution. We believe the latter, but the answer will only come with further development of an Ecology

of Information Framework, one that integrates all the sub-disciplines in Figure 1. Through our overview

and the papers that follow in this special feature on the Ecology of Information, we hope to have …….

ACKNOWLEDGEMENTS (566)

KAS’s research in the ecology of information is supported by a grant from the National Science

Foundation (DEB 0746985). JAvG was supported by the Netherlands Organization for Scientific

Research (NWO) and by the Royal Netherlands Academy of Arts and Sciences (KNAW). This is

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publication xxxx of the Netherlands Institute of Ecology (NIOO-KNAW) and xxx of the Centre for

Wetland Ecology. This paper was improved by comments of Luc-Alain Giraldeau and an anonymous

reviewer. Lastly, we are grateful to Per Lundberg and Linus Svensson for their support of this special

feature.

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FIGURE LEGENDS

Figure 1: Domains of the disciplines that investigate information in biology at the organism-level. The

figure is adapted in part from Koops (1998).

Figure 2: Consider information as a change in the probability (; or probability distribution) of an event

or state, e.g., might be a prey’s estimate of the probability a predator is present in a forest patch

occupied by the prey or male quality as judged by a female’s observations of male display. An individual

has a prior estimate, PR, which is altered (PO; posterior) as information is processed from an observation

(e.g., an alarm call). PO decays over time (this functional form is illustrated as D) as information is

temporally discounted, and eventually settles back to the prior value (PR). The form of the decay curve

will be highly variable and specific to context. Information may be used to permanently assign a state

(e.g., an individual’s gender or a fishless pond) that may result in a permanent developmental switch

(polyphenism) or time its development . Alternatively, states repeatedly cycle between states in

time or space (behavioral). Lastly, norm of reaction

Evolutionary traps are produced when one or more of these three responses (PR, PO, and D) no longer

matches its environment because the type or reliability of the cue or the state it ‘refers’ to has changed.

Figure 3: Mean persistence time ( SE) as a function of the number of component patches in the network

in a temporal autocorrelated landscape ( = 0.7). Dispersal is even (black line) or using the WSLS rule

(for more details see Schmidt 2004).

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1041

1042

1043

1044

1045

1046

1047

1048

1049

1050

1051

1052

1053

1054

1055

1056

1057

1058

1059

1060

1061

1062

1063

35

FIGURE 1

Information Source

Reception

Perception

Decision, i.e., response of the receiver

Transmission

Translation

Evaluation

Behavioral , developmental and life history changes

Populations

Communities

Ecosystems

Consequence(public info)

Evolutionary Ecology

Sensory ecology,Cognition, Psychology

Evolution(genetic info)

36

10641065

1066106710681069107010711072

36

FIGURE 2

37

1073107410751076

1077107810791080

37

FIGURE 3

Even dispersal, rho = 0.7

2 3 4 5 6 7 8

Number of patches

0

500

1000

1500

2000

WSLS, rho = 0.7

Mea

n po

pula

tion

pers

isten

ce (y

rs)

38

1081108210831084

108510861087108810891090109110921093

38

Box 1: Glossary of terms: Note, these definitions closely follow Wagner and Danchin (this issue)

Cues – A detectable fact that is non-intentionally produced. Includes facts produced by physical agents

or inadvertently produced by biological agents.

Signals – A trait or behavior of a signaler evolved specifically to alter the behavior of the receiver in a

way to benefit the signaler. The change in receiver behavior should also have evolved to enhanced

receiver fitness.

Public information – Information that is in the public domain and potentially available to any organism.

Private information - Information that is undetectable to other organisms through direct means. Private

information may become public through indirect means. This follows a sequence (using the model by

Seppänen et al. 2007): 1) observation of an event or state by a primary observer; 2) a decision that is

manifest via change in behavior (i.e., an action) of the primary observer; 3) the consequence of the

action. For example, Wong et al. (2005) demonstrated that sand fiddler crabs (Uca pugilator) use

observations of threat-induced responses of neighbors (stage 2 in the sequence above) to guide their

own refuge-seeking behavior. Birds settling on territories where conspecific reproductive success was

high in prior years (see Breeding habitat selection) is an example of observing the consequences (stage

3) of past decisions by conspecifics.

Socially acquired Information – Information extracted from other individuals (con- or heterospecific) be

they signals or (inadvertent) cues (including actions and consequences). Note: all social information

must be public.

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10941095

1096

1097

1098

1099

1100

1101

1102

1103

1104

1105

1106

1107

1108

1109

1110

1111

1112

1113

1114

1115

1116

1117

39

Interceptive and Social Eavesdropping (Peake 2005) – A mechanism of acquiring social information from

signals (i.e., communication) between two (or more) individuals. In interceptive eavesdropping

individuals acquire information about their environment (e.g., an alarm call gives information about the

presence of a predator), whereas in social eavesdropping individuals acquire information regarding the

social relationship between the communicating parties (e.g., dominance hierarchy, kinship).

40

1118

1119

1120

1121

1122

1123

40

Box 2: Breeding habitat selection/settlement strategies as a function of spatial heterogeneity and

temporal predictability. Four regions are identified across what is in reality a continuum. In the top

row, high variation in individual (fine scale) site quality exists, whereas patch quality, averaged over the

many individual sites it contains, is low. Fidelity to successful sites is favored provided temporal

predictability is high (top right). Likewise, dispersal from unsuccessful sites is favored and individuals

should prospect for future sites not patches since patch reproductive success has little spatial variation.

We call this the win-stay, lose-prospect strategy (WSLP). When spatial variation is higher between

patches than sites (bottom row) individuals should prospect for information on patch reproductive

success provided temporal predictability is high (bottom right). Fidelity or dispersal should be linked

closely to patch reproductive success rather than an individual’s own success. When temporal

predictability is low an individual should prospect during the pre-breeding season for current, proximate

cues of reproductive potential at the scale of greatest spatial: at sites (top left) or patches (bottom left).

Conspecific attraction is only favored when spatial variation is higher between patches than sites,

assuming individuals preempt sites by occupation. It further requires that some individuals (call them

prospectors) use patch reproductive success as a settlement cue. In other words, conspecific attraction

is an information-scrounger strategy that requires information collected by the information-producer

strategy of prospectors (Dall et al. 2005).

41

1124

1125

1126

1127

1128

1129

1130

1131

1132

1133

1134

1135

1136

1137

1138

1139

1140

114111421143

41

BOX 2

Spati

al

hete

roge

neity

temporal predictability

Fine:site > patch

Coarse:patch > site

low high

(1)

(3)

(2)

(4)

PRS high

PRS

Fidelity: to siteInfo: pers. repro. successConspecific attraction: noProspect: pre- or post-breeding; prospect at sites

Fidelity: noneInfo: noneConspecific attraction: noProspect: pre-breeding; prospect at sites

Fidelity: to patch Info: patch repro. successConspecific attraction: yesProspect: pre- or post-breeding; prospect at patches

Fidelity: noneInfo: noneConspecific attraction: ?Prospect: pre-breeding; Prospect at patches

Site

Patch

42

1144114511461147

114811491150115111521153115411551156115711581159

42