ArticlePublisher preview availableLiterature Review

The fitness value of ecological information in a variable world

February 2023
Ecology Letters 26(4):n/a-n/a

Authors:

University of British Columbia

Information processing is increasingly recognized as a fundamental component of life in variable environments, including the evolved use of environmental cues, biomolecular networks, and social learning. Despite this, ecology lacks a quantitative framework for understanding how population, community, and ecosystem dynamics depend on information processing. Here, we review the rationale and evidence for ‘fitness value of information’ (FVOI), and synthesize theoretical work in ecology, information theory, and probability behind this general mathematical framework. The FVOI quantifies how species' per capita population growth rates can depend on the use of information in their environment. FVOI is a breakthrough approach to linking information processing and ecological and evolutionary outcomes in a changing environment, addressing longstanding questions about how information mediates the effects of environmental change and species interactions.

Conceptual layout of the fitness value of information (FVOI): see Box 1 for more details. (a) Populations recover from low density more quickly when information is present and they have an internal model of the frequency of favourable environments. The FVOI (Δ𝜌i) is measured as the difference between informed and uninformed population (log) growth rates. (b) Patterns of environmental variation may serve as a cue for favourable environments, as when the amount of early‐season precipitation (e.g. in January) signals the total amount of rain that will fall during the growing season. (c–e) The FVOI framework parses the information in the environment using information‐theoretic metrics, using frequency distributions of environmental patterns. (c) The Shannon Entropy measures the “surprisal” of a single variable (total rain). (d) The KL divergence provides a measure of the difference of the distributions of two variables (a statistical distance); bin‐by‐bin differences between two variables (early and late year precipitation) are pictured as dark grey bars. (e) Information gained by a variable by observing a second variable is measured by the mutual information (MI). Surface plots show the join probability distribution of two variables, whose individual (marginal) probabilities are shown along the edges. (f–h) The FVOI parses the population's internal model using the same information theoretic metrics. (f) Populations can exploit MI between two variables by treating one variable as a cue. (g) In this example, high MI produces a reliable cue used by seeds of an annual plant species to initiate germination. (h) How efficiently a population uses this information can be measured by comparing the population‐level proportion of germinants in each environment against the actual distribution of environments. Then, Δ𝜌i is the difference between the MI (f) and the KL divergence of environment and internal model (h).

…

Population growth for two life history models: (a) a simple multiplicative process and (b) the dormancy model. Each model allows for a strategy or phenotype to reproduce without environmental information 𝜌i(E), or to use an environmental cue for information 𝜌i(E|C) (see text and model details in Box 1). To illustrate the relative contributions of I(E;C) and each population to the FVOI, values of the slopes 𝜌i(E) and 𝜌i(E|C) are shown in (c) and (d) for each model. The fitness value of information is measured by the difference between the two slopes Δ𝜌i. The mutual information I(E;C) between the environment and the cue defines the maximum potential contribution of a cue to fitness, while the KL Divergence (DKL) quantifies the extent to which a population fails to benefit from an informative cue; the stacked bars in (c) and (d) illustrate that the FVOI is the difference between I(E;C) and DKL. See the Appendix S1 for simulation details.

…

The dynamics of the lottery model (a) for a population of species 1 (shown in green) in the presence of a competitor (in purple) with and without the ability to detect an environmental cue that helps it predict favourable environmental conditions for germination (see Box 2 for model description). (b) The environment is simulated by taking draws from a normal distribution to set the conditions for each time step, without autocorrelation (μ = 0.5 and σ = 0.1, b). Each species (green and purple lines) has a different optimum environment modelled as Gaussian curves so that reproductive fitness decays with the distance of an environmental state from the optimum. (c) The varying environmental state, reproduction, and germination rates are simulated as a time series. When germination is informed (because 𝜌i(E|C) is high) then germination rates match closely to the reproduction rates in that year, as seen in the solid germination lines. When germination is not informed then there is no correlation between germination rates and reproduction; this is seen by comparing the dotted germination lines to the reproduction rates. See the Appendix S1 for simulation code.

…

The change in the fitness value of information for two species (one green, one purple) competing for fluctuating resources. Competition increases with more resource overlap because species will reproduce more often under similar conditions and limit the growth of the other. (a) The fitness value of information Δ𝜌i for each species decreases when competition for resources increases. (b) The niche difference between the two species when both species use information, or when both species are uninformed (i.e. 𝜌i(E|C) and 𝜌i(E)) as labelled. A niche difference of 1 corresponds with 100% differentiation.

…

The population dynamics of the competition model with social information, with (upper lines) and without (lower lines) social information.

…

Figures - available from: Ecology Letters

This content is subject to copyright. Terms and conditions apply.

A preview of this full-text is provided by Wiley.

Learn more

Content available from Ecology Letters

This content is subject to copyright. Terms and conditions apply.

Ecolog y Letters. 2023;26:621– 639. wileyonlinelibrary.com/journal/ele

621

QUANTIFYING INFORMATION

IN ECOLOGY

Biology is built upon information. From genetic architec-

ture (Goldenfeld & Woese,2007; Smith,1999; Tkačik &

Bialek,2016), to sub- cellular biomolecular networks (Cai

et al.,2018; Tyson et al.,2002; Woods & Wilson, 2013),

to the countless examples of derived sensory apparatus

in organisms, life is replete with systems and mecha-

nisms for detecting, processing, and storing information

(Dangles et al.,2009). Natural selection itself is an infor-

mation process, where changing gene frequencies encode

population- level information about the fitness conse-

quences of the environment (Frank,2012; Smith,1999).

Ecological studies account for myriad ways that organ-

isms across all kingdoms of life respond to changing

environments and use cues in their environment to find

resources, refuges, and reproduce (Crespi, 2001; Crone

et al.,2009; Gil et al.,2018). However, accounting for the

explicit role that information plays in population, com-

munity, and ecosystem dynamics remains a largely unex-

plored research frontier (Marleau et al.,2020; O'Connor

et al.,2019).

Information is increasingly acknowledged as a uni-

versal and essential component to life in fluctuating

environments (Bernhardt et al.,2020). Historically, in-

formation has been equated with a variety of environ-

mental cues. These include environmental changes that

trigger phenological shifts (Clauss & Venable, 2000;

Cohen,1966; Pake & Venable, 1996; Ten Brink et al.,2020;

Thackeray et al.,2016), social or chemical signals used to

find food (Danchin et al.,2004; Gil et al.,2018; Magrath

et al., 2015), shared between bacteria to monitor local

densities (Crespi,2001), or transmitted between plants as

volatile organic compounds triggered by defence against

herbivor (Baldwin et al.,2006; De Moraes et al.,1998).

While these important studies have guided scientific

progress, taken collectively they create an idiosyncratic,

system- specific perspective on information that has pre-

cluded generalization. Furthermore, they tend to lack a

dynamical framing of information's role.

A generalizable definition of information that cap-

tures the functional role of biological cue s can be found in

information theory (Goldenfeld & Woese,2007; Tkačik

& Bialek, 2016). In information theory, information is

measured in relation to the uncertainty or “surprisal”

of an event. Observing a less- probable (more surprising)

event is more valuable precisely because there are fewer

opportunities to do so and an observer will be better-

informed after a rare event than after a common event.

SYNTHESIS

The fitness value of ecological information in a variable world

JacobUsinowicz1,2 | Mary I.O'Connor1, 2

Received: 16 September 2021

Revised: 8 December 2022

Accepted: 8 December 2022

DOI: 10.1111/ele.14166

1Department of Zoolog y, University of

British Columbia, Vancouver, Canada

2Biodiversity Research Centre, University

of British Columbia, Vancouver, Canada

Correspondence

Jacob Usinowicz, Department of

Zoology, 4200- 6270 University Boulevard,

Vancouver, BC V6T 1Z4, Canada.

Email: jusinowicz@gmail.com

Funding information

Natural Sciences and Engineering research

Council of Canada (NSERC) / EWR

Steacie Fellowship, Grant/Award Numb er:

SMFSU 54147- 2020; NSERC Discovery

Accelerator Supplement (DAS)

Editor: Robin Snyder

Abstract

Information processing is increasingly recognized as a fundamental component

of life in variable environments, including the evolved use of environmental

cues, biomolecular networks, and social learning. Despite this, ecology lacks

a quantitative framework for understanding how population, community, and

ecosystem dynamics depend on information processing. Here, we review the

rationale and evidence for ‘fitness value of information’ (FVOI), and synthesize

theoretical work in ec ology, information theory, and probability behind this general

mathematical framework. The FVOI quantifies how species' per capita population

growth rates can depend on the use of information in their environment. FVOI

is a breakthrough approach to linking information processing and ecological

and evolutionary outcomes in a changing environment, addressing longstanding

questions about how information mediates the effects of environmental change

and species interactions.

KEYWOR DS

coexistence, community dynamics, ecology, fitness, information theory, population

The interplay between abiotic and biotic factors in dispersal decisions in metacommunities

Article

Full-text available

Jun 2024
PHILOS T R SOC B

Suitable conditions for species to survive and reproduce constitute their ecological niche, which is built by abiotic conditions and interactions with conspecifics and heterospecifics. Organisms should ideally assess and use information about all these environmental dimensions to adjust their dispersal decisions depending on their own internal conditions. Dispersal plasticity is often considered through its dependence on abiotic conditions or conspecific density and, to a lesser extent, with reference to the effects of interactions with heterospecifics, potentially leading to misinterpretation of dispersal drivers. Here, we first review the evidence for the effects of and the potential interplays between abiotic factors, biotic interactions with conspecifics and heterospecifics and phenotype on dispersal decisions. We then present an experimental test of these potential interplays, investigating the effects of density and interactions with conspecifics and heterospecifics on temperature-dependent dispersal in microcosms of Tetrahymena ciliates. We found significant differences in dispersal rates depending on the temperature, density and presence of another strain or species. However, the presence and density of conspecifics and heterospecifics had no effects on the thermal-dependency of dispersal. We discuss the causes and consequences of the (lack of) interplay between the different environmental dimensions and the phenotype for metacommunity assembly and dynamics. This article is part of the theme issue ‘Diversity-dependence of dispersal: interspecific interactions determine spatial dynamics’.

Integrating learning into animal range dynamics under rapid human‐induced environmental change

Article

Full-text available

Feb 2024
ECOL LETT

Human‐induced rapid environmental change (HIREC) is creating environments deviating considerably from natural habitats in which species evolved. Concurrently, climate warming is pushing species’ climatic envelopes to geographic regions that offer novel ecological conditions. The persistence of species is likely affected by the interplay between the degree of ecological novelty and phenotypic plasticity, which in turn may shape an organism's range‐shifting ability. Current modelling approaches that forecast animal ranges are characterized by a static representation of the relationship between habitat use and fitness, which may bias predictions under conditions imposed by HIREC. We argue that accounting for dynamic species‐resource relationships can increase the ecological realism of range shift predictions. Our rationale builds on the concepts of ecological fitting, the process whereby individuals form successful novel biotic associations based on the suite of traits they carry at the time of encountering the novel condition, and behavioural plasticity, in particular learning. These concepts have revolutionized our view on fitness in novel ecological settings, and the way these processes may influence species ranges under HIREC. We have integrated them into a model of range expansion as a conceptual proof of principle highlighting the potentially substantial role of learning ability in range shifts under HIREC.

Semantic Information in a Model of Resource Gathering Agents

Article

Full-text available

Oct 2023

We explore the application of a theory of semantic information to the well-motivated problem of resource foraging. Semantic information is defined as the subset of correlations, which is here measured via the transfer entropy, between agent A and environment E that is necessary for the agent to maintain its viability V. Viability, in turn, is endogenously defined as opposed to the use of exogenous quantities like utility functions. In our model, the forager's movements are determined by its ability to measure, via a sensor, the presence of an individual unit of resource, while the viability function is its expected lifetime. Through “interventions”—scrambling the correlations between agent and environment by noising the sensor—we demonstrate the presence of a critical value of the noise parameter, ηc, above which the forager's expected lifetime is dramatically reduced. On the other hand, for η<ηc there is little to no effect on its ability to survive. We refer to this boundary as the semantic threshold, quantifying the subset of agent-environment correlations that the agent actually needs to maintain its desired state of staying alive. Each bit of information affects the agent's ability to persist both above and below the semantic threshold. Modeling the viability curve and its semantic threshold via forager and/or environment parameters, we show how the correlations are instantiated. Our work demonstrates the successful application of semantic information to a well-known agent-based model of biological and ecological interest. Additionally, we demonstrate that the concept of semantic thresholds may prove useful for understanding the role information plays in allowing systems to become autonomous agents.

Life in fluctuating environments

Article

Full-text available

Nov 2020

Variability in the environment defines the structure and dynamics of all living systems, from organisms to ecosystems. Species have evolved traits and strategies that allow them to detect, exploit and predict the changing environment. These traits allow organisms to maintain steady internal conditions required for physiological functioning through feedback mechanisms that allow internal conditions to remain at or near a set-point despite a fluctuating environment. In addition to feedback, many organisms have evolved feedforward processes, which allow them to adjust in anticipation of an expected future state of the environment. Here we provide a framework describing how feedback and feedforward mechanisms operating within organisms can generate effects across scales of organization, and how they allow living systems to persist in fluctuating environments. Daily, seasonal and multi-year cycles provide cues that organisms use to anticipate changes in physiologically relevant environmental conditions. Using feedforward mechanisms, organisms can exploit correlations in environmental variables to prepare for anticipated future changes. Strategies to obtain, store and act on information about the conditional nature of future events are advantageous and are evidenced in widespread phenotypes such as circadian clocks, social behaviour, diapause and migrations. Humans are altering the ways in which the environment fluctuates, causing correlations between environmental variables to become decoupled, decreasing the reliability of cues. Human-induced environmental change is also altering sensory environments and the ability of organisms to detect cues. Recognizing that living systems combine feedback and feedforward processes is essential to understanding their responses to current and future regimes of environmental fluctuations. This article is part of the theme issue ‘Integrative research perspectives on marine conservation’.

A unifying, eco‐physiological framework for animal dormancy

Article

Full-text available

Dec 2020
FUNCT ECOL

Various animals across the tree of life express some form of programmed dormancy (e.g. hibernation, diapause) to maximize fitness in highly seasonal environments. The integrated phenotype of animals undergoing programmed dormancy is strikingly similar among diverse groups; however, research on programmed dormancy has historically been phylogenetically siloed. A broad comparative approach could clarify new angles for answering fundamental questions about programmed dormancy evolution. To advance this approach, we present a cross‐taxonomic framework describing dimensions that distinguish animal dormancies and provide a set of core traits that animals regulate as they progress through the eco‐physiological phases of deep, programmed dormancy. We use this universal framework to explore the ultimate drivers and evolutionary consequences of dormancy across the tree of life. Deep, programmed dormancy appears to be a predictable and repeated adaptation to highly seasonal environments that draws on a conserved suite of ancestral traits. We highlight evidence for molecular convergence in signalling pathways coordinating environmental sensing and energy metabolism in the insect and mammal lineages, separated by 700 million years of evolution and representing independent colonizations of highly seasonal environments. Lastly, we discuss the utility of this new framework and highlight opportunities and challenges for researchers to continue advancing our understanding of dormancy through a broad, comparative lens. A free Plain Language Summary can be found within the Supporting Information of this article.

Mixed company: a framework for understanding the composition and organization of mixed-species animal groups

Article

Full-text available

Feb 2020

Mixed-species animal groups (MSGs) are widely acknowledged to increase predator avoidance and foraging efficiency, among other benefits, and thereby increase participants' fitness. Diversity in MSG composition ranges from two to 70 species of very similar or completely different phenotypes. Yet consistency in organization is also observable in that one or a few species usually have disproportionate importance for MSG formation and/or maintenance. We propose a two-dimensional framework for understanding this diversity and consistency, concentrating on the types of interactions possible between two individuals, usually of different species. One axis represents the similarity of benefit types traded between the individuals, while the second axis expresses asymmetry in the relative amount of benefits/costs accrued. Considering benefit types, one extreme represents the case of single-species groups wherein all individuals obtain the same supplementary, group-size-related benefits, and the other extreme comprises associations of very different, but complementary species (e.g. one partner creates access to food while the other provides vigilance). The relevance of social information and the matching of activities (e.g. speed of movement) are highest for relationships on the supplementary side of this axis, but so is competition; relationships between species will occur at points along this gradient where the benefits outweigh the costs. Considering benefit amounts given or received, extreme asymmetry occurs when one species is exclusively a benefit provider and the other a benefit user. Within this parameter space, some MSG systems are constrained to one kind of interaction, such as shoals of fish of similar species or leader-follower interactions in fish and other taxa. Other MSGs, such as terrestrial bird flocks, can simultaneously include a variety of supplementary and complementary interactions. We review the benefits that species obtain across the diversity of MSG types, and argue that the degree and nature of asymmetry between benefit providers and users should be measured and not just assumed. We then discuss evolutionary shifts in MSG types, focusing on drivers towards similarity in group composition, and selection on benefit providers to enhance the benefits they can receive from other species. Finally, we conclude by considering how individual and collective behaviour in MSGs may influence both the structure and processes of communities.

Optimal germination timing in unpredictable environments: the importance of dormancy for both among‐ and within‐season variation

Article

Full-text available

Jan 2020
ECOL LETT

For organisms living in unpredictable environments, timing important life‐history events is challenging. One way to deal with uncertainty is to spread the emergence of offspring across multiple years via dormancy. However, timing of emergence is not only important among years, but also within each growing season. Here, we study the evolutionary interactions between germination strategies that deal with among‐ and within‐season uncertainty. We use a modelling approach that considers among‐season dormancy and within‐season germination phenology of annual plants as potentially independent traits and study their separate and joint evolution in a variable environment. We find that higher among‐season dormancy selects for earlier germination within the growing season. Furthermore, our results indicate that more unpredictable natural environments can counter‐intuitively select for less risk‐spreading within the season. Furthermore, strong priority effects select for earlier within‐season germination phenology which in turn increases the need for bet hedging through among‐season dormancy. Here, we use a modelling approach to study the evolution of germination timing in annual plants living in unpredictable conditions. We find that when natural environments become more unpredictable, this counterintuitively leads to less within‐season bet hedging. Furthermore, in the presence of priority effects it is beneficial to spread germination over multiple years even when every growing season is favorable for reproduction.

Phenology of nocturnal avian migration has shifted at the continental scale

Article

Full-text available

Jan 2020
Nat. Clim. Change.

Climate change induced phenological shifts in primary productivity result in trophic mismatches for many organisms1–4, with broad implications for ecosystem structure and function. For birds that have a synchronized timing of migration with resource availability, the likelihood that trophic mismatches may generate a phenological response in migration timing increases with climate change5. Despite the importance of a holistic understanding of such systems at large spatial and temporal scales, particularly given a rapidly changing climate, analyses are few, primarily because of limitations in the access to appropriate data. Here we use 24 years of remotely sensed data collected by weather surveillance radar to quantify the response of a nocturnal avian migration system within the contiguous United States to changes in temperature. The average peak migration timing advanced in spring and autumn, and these changes were generally more rapid at higher latitudes. During spring and autumn, warmer seasons were predictive of earlier peak migration dates. Decadal changes in surface temperatures predicted spring changes in migratory timing, with greater warming related to earlier arrivals. This study represents one of the first system-wide examinations during two seasons and comprises measures from hundreds of species that describe migratory timing across a continent. Our findings provide evidence of spatially dynamic phenological shifts that result from climate change. Climate change affects the timing of bird migration, which can lead to mismatch with resource availability. Migration occurred earlier in spring and autumn in the United States during the past 24 years; warming led to later arrival in the western Unites States and earlier arrival in the rest of the country.

Niche and fitness differences relate the maintenance of diversity to ecosystem function

Article

May 2011

http://deepblue.lib.umich.edu/bitstream/2027.42/116920/1/ecy20119251157.pdf

MASTING BY EIGHTEEN NEW ZEALAND PLANT SPECIES: THE ROLE OF TEMPERATURE AS A SYNCHRONIZING CUE

Article

May 2002

Fast behavioral feedbacks make ecosystems sensitive to pace and not just magnitude of anthropogenic environmental change

Article

Sep 2020
P NATL ACAD SCI USA

Significance Human activities can alter the behavior of wildlife. Although behavior is known to affect species interactions and demography, behavioral feedbacks are often absent from the types of population models used to understand how ecosystems respond to anthropogenic change. We show that incorporating empirically measured fish feeding behavior into dynamical models of a coral reef alters how the ecosystem responds to fishing. Fish behavior can cause ecosystem collapse in response to less fishing but also, unexpectedly, to subtle differences in the pace at which fishing increases. Behavioral mechanisms similar to those included in our model are present in many ecological systems, and our findings suggest these mechanisms could inform both fundamental understanding and management strategies in such systems.

Converting Ecological Currencies: Energy, Material, and Information Flows

Article

Sep 2020

Understanding how the three currencies of life - energy, material, and information - interact is a key step towards synthesis in ecology and evolution. However, current theory focuses on the role of matter as a resource and energy, and typically ignores how the same matter can have other important effects as a carrier of information or modifier of the environment. Here we present the hypothesis that the dynamic conversion of matter by organisms among its three currencies mediates the structure and function of ecosystems, and that these effects can even supersede the effects of matter as a resource. Humans are changing the information in the environment and this is altering species interactions and flows of matter within and among ecosystems.

Phenological responses of temperate and boreal trees to warming depend on ambient spring temperatures, leaf habit, and geographic range

Article

Apr 2020

Changes in plant phenology associated with climate change have been observed globally. What is poorly known is whether and how phenological responses to climate warming will differ from year to year, season to season, habitat to habitat, or species to species. Here, we present 5 y of phenological responses to experimental warming for 10 subboreal tree species. Research took place in the open-air B4WarmED experiment in Minnesota. The design is a two habitat (understory and open) × three warming treatments (ambient, +1.7 °C, +3.4 °C) factorial at two sites. Phenology was measured twice weekly during the growing seasons of 2009 through 2013. We found significant interannual variation in the effect of warming and differences among species in response to warming that relate to geographic origin and plant functional group. Moreover, responses to experimental temperature variation were similar to responses to natural temperature variation. Warming advanced the date of budburst more in early compared to late springs, suggesting that to simulate interannual variability in climate sensitivity of phenology, models should employ process-based or continuous development approaches. Differences among species in timing of budburst were also greater in early compared to late springs. Our results suggest that climate change—which will make most springs relatively “early”—could lead to a future with more variable phenology among years and among species, with consequences including greater risk of inappropriately early leafing and altered interactions among species.

The fitness value of ecological information in a variable world

Abstract and Figures

Recommended publications

An expanded modern coexistence theory for empirical applications

Limited Dispersal Drives Clustering and Reduces Coexistence by the Storage Effect

Species persistence under climate change: a geographical scale coexistence problem

Climate‐driven range shifts reduce persistence of competitors in a perennial plant community