The small-bat-in-summer paradigm: Energetics and adaptive behavioural routines of bats investigated through a stochastic dynamic model.

Strong seasonality at high latitudes represents a major challenge for many endotherms as they must balance survival and reproduction in an environment that varies widely in food availability and temperature. To avoid energetic mismatches caused by limited foraging time and stochastic weather conditions, bats employ the energy-saving state of torpor during summer to save accumulated energy reserves. However, at high-latitude small-bats-in-summer face a particular challenge: as nocturnal foragers, they rely on the darkness at night to avoid predators and/or interspecific competition, but live in an environment with short, light summer nights, and even a lack of true night at the northernmost distributions of some bat species. To predict optimal behaviour in relation to latitudinal variation in diurnal cycles, we constructed a stochastic dynamic programming model of bats living at high latitudes. Using a stochastic dynamic programming framework with values that are representative for our study system, we show that individual energetic reserves are a strong driver of daytime use of torpor and night-time foraging behaviour alike, with these linked effects being both temperature- and photoperiod-dependent. We further used the model to predict survival probabilities at five locations across a latitudinal gradient (60.1° N to 70.9° N), finding that combinations of photoperiod and temperature conditions limited population distributions in the model. To verify our model results, we compared predictions for optimal decisions with our own empirical data collected on northern bats (Eptesicus nilssonii) from two latitudes in Norway. The similarities between our predictions and observations provide strong evidence that this model framework incorporates the most important drivers of diurnal decision-making in bat physiology and behaviour. Comparing empirical data and model predictions also revealed that bats facing lighter night conditions further north restrict their mass gain, which strengthens the hypothesis that predation threat is a main driver of bat nocturnality. Our model findings regarding state-dependent decisions in bats should contribute to the understanding of how bats cope with the summer challenges at high latitudes.

Plant environmental memory: implications, mechanisms and opportunities for plant scientists and beyond.

Plants are extremely plastic organisms. They continuously receive and integrate environmental information and adjust their growth and development to favour fitness and survival. When this integration of information affects subsequent life stages or the development of subsequent generations, it can be considered an environmental memory. Thus, plant memory is a relevant mechanism by which plants respond adaptively to different environments. If the cost of maintaining the response is offset by its benefits, it may influence evolutionary trajectories. As such, plant memory has a sophisticated underlying molecular mechanism with multiple components and layers. Nonetheless, when mathematical modelling is combined with knowledge of ecological, physiological, and developmental effects as well as molecular mechanisms as a tool for understanding plant memory, the combined potential becomes unfathomable for the management of plant communities in natural and agricultural ecosystems. In this review, we summarize recent advances in the understanding of plant memory, discuss the ecological requirements for its evolution, outline the multilayered molecular network and mechanisms required for accurate and fail-proof plant responses to variable environments, point out the direct involvement of the plant metabolism and discuss the tremendous potential of various types of models to further our understanding of the plant's environmental memory. Throughout, we emphasize the use of plant memory as a tool to unlock the secrets of the natural world.

Environmental change and the rate of phenotypic plasticity.

With rapid and less predictable environmental change emerging as the 'new norm', understanding how individuals tolerate environmental stress via plastic, often reversible changes to the phenotype (i.e., reversible phenotypic plasticity, RPP), remains a key issue in ecology. Here, we examine the potential for better understanding how organisms overcome environmental challenges within their own lifetimes by scrutinizing a somewhat overlooked aspect of RPP, namely the rate at which it can occur. Although recent advances in the field provide indication of the aspects of environmental change where RPP rates may be of particular ecological relevance, we observe that current theoretical models do not consider the evolutionary potential of the rate of RPP. Whilst recent theory underscores the importance of environmental predictability in determining the slope of the evolved reaction norm for a given trait (i.e., how much plasticity can occur), a hitherto neglected possibility is that the rate of plasticity might be a more dynamic component of this relationship than previously assumed. If the rate of plasticity itself can evolve, as empirical evidence foreshadows, rates of plasticity may have the potential to alter the level predictability in the environment as perceived by the organism and thus influence the slope of the evolved reaction norm. However, optimality in the rate of phenotypic plasticity, its evolutionary dynamics in different environments and influence of constraints imposed by associated costs remain unexplored and may represent fruitful avenues of exploration in future theoretical and empirical treatments of the topic. We conclude by reviewing published studies of RPP rates, providing suggestions for improving the measurement of RPP rates, both in terms of experimental design and in the statistical quantification of this component of plasticity.

Individual reversible plasticity as a genotype-level bet-hedging strategy.

Reversible plasticity in phenotypic traits allows organisms to cope with environmental variation within lifetimes, but costs of plasticity may limit just how well the phenotype matches the environmental optimum. An additional adaptive advantage of plasticity might be to reduce fitness variance, in other words: bet-hedging to maximize geometric (rather than simply arithmetic) mean fitness. Here, we model the evolution of plasticity in the form of reaction norm slopes, with increasing costs as the slope or degree of plasticity increases. We find that greater investment in plasticity (i.e. a steeper reaction norm slope) is favoured in scenarios promoting bet-hedging as a response to multiplicative fitness accumulation (i.e. coarser environmental grains and fewer time steps prior to reproduction), because plasticity lowers fitness variance across environmental conditions. In contrast, in scenarios with finer environmental grain and many time steps prior to reproduction, bet-hedging plays less of a role and individual-level optimization favours evolution of shallower reaction norm slopes. However, the opposite pattern holds if plasticity costs themselves result in increased fitness variation, as might be the case for production costs of plasticity that depend on how much change is made to the phenotype each time step. We discuss these contrasting predictions from this partitioning of adaptive plasticity into short-term individual benefits versus long-term genotypic (bet-hedging) benefits, and how this approach enhances our understanding of the evolution of optimum levels of plasticity in examples from thermal physiology to advances in avian lay dates.

Bet-hedging across generations can affect the evolution of variance-sensitive strategies within generations.

In order to understand how organisms cope with ongoing changes in environmental variability, it is necessary to consider multiple adaptations to environmental uncertainty on different time scales. Conservative bet-hedging (CBH) represents a long-term genotype-level strategy maximizing lineage geometric mean fitness in stochastic environments by decreasing individual fitness variance, despite also lowering arithmetic mean fitness. Meanwhile, variance-prone (aka risk-prone) strategies produce greater variance in short-term payoffs, because this increases expected arithmetic mean fitness if the relationship between payoffs and fitness is accelerating. Using evolutionary simulation models, we investigate whether selection for such variance-prone strategies is counteracted by selection for bet-hedging that works to adaptively reduce fitness variance. In our model, variance proneness evolves in fine-grained environments (lower correlations among individuals in energetic state and/or payoffs), and with larger numbers of independent decision events over which resources accumulate prior to selection. Conversely, multiplicative fitness accumulation, caused by coarser environmental grain and fewer decision events selection, favours CBH via greater variance aversion. We discuss examples of variance-sensitive strategies in optimal foraging, migration, life histories and cooperative breeding using this bet-hedging perspective. By linking disparate fields of research studying adaptations to variable environments, we should be better able to understand effects of human-induced rapid environmental change.

The coevolution of lifespan and reversible plasticity.

Reversible phenotypic plasticity, the ability to change one's phenotype repeatedly throughout life, can be selected for in environments that do not stay constant throughout an individual's lifetime. It might also mitigate senescence, as the mismatch between the environment and a non-plastic individual's traits is likely to increase as time passes. To understand why reversible plasticity may covary with lifespan, studies tend to assume unidirectional causality: plasticity evolves under suitable rates of environmental variation with respect to life history. Here we show that if lifespan also evolves in response to plasticity, then long life is not merely a context that sets the stage for lifelong plasticity. Instead, the causality is bidirectional because plasticity itself can select for longevity. Highly autocorrelated environmental fluctuations predict low investment in reversible plasticity and a phenotype that is poorly matched to the environment at older ages. Such environments select for high reproductive effort and short lifespans.

How to quantify thermal acclimation capacity?

The capacity of organisms to acclimate will influence their ability to cope with ongoing global changes in thermal regimes. Here we highlight methodological issues associated with recent attempts to quantify variation in acclimation capacity among taxa and environments, and describe how these may introduce bias to conclusions. We then propose a measure of thermal acclimation capacity that more directly quantifies the process of acclimation. Future studies of variation in acclimation capacity should critically evaluate whether their chosen empirical metric accurately reflects the theoretical concept of acclimation.

Short-term insurance versus long-term bet-hedging strategies as adaptations to variable environments.

Understanding how organisms adapt to environmental variation is a key challenge of biology. Central to this are bet-hedging strategies that maximize geometric mean fitness across generations, either by being conservative or diversifying phenotypes. Theoretical models have identified environmental variation across generations with multiplicative fitness effects as driving the evolution of bet-hedging. However, behavioral ecology has revealed adaptive responses to additive fitness effects of environmental variation within lifetimes, either through insurance or risk-sensitive strategies. Here, we explore whether the effects of adaptive insurance interact with the evolution of bet-hedging by varying the position and skew of both arithmetic and geometric mean fitness functions. We find that insurance causes the optimal phenotype to shift from the peak to down the less steeply decreasing side of the fitness function, and that conservative bet-hedging produces an additional shift on top of this, which decreases as adaptive phenotypic variation from diversifying bet-hedging increases. When diversifying bet-hedging is not an option, environmental canalization to reduce phenotypic variation is almost always favored, except where the tails of the fitness function are steeply convex and produce a novel risk-sensitive increase in phenotypic variance akin to diversifying bet-hedging. Importantly, using skewed fitness functions, we provide the first model that explicitly addresses how conservative and diversifying bet-hedging strategies might coexist.

Differential allocation of parental investment and the trade-off between size and number of offspring.

When parents decide how much to invest in current versus future offspring and how many offspring to divide their current investments between, the optimal decision can be affected by the quality of their partner. This differential allocation (DA) is highly dependent on exactly how partner quality affects reproductive costs and offspring benefits. We present a stochastic dynamic model of DA in which females care for a series of clutches when mated with males of different quality. In each reproductive event, females choose the size and number of offspring. We find that if partner quality affects reproductive costs, then DA in total reproductive investment occurs only via changes in the number of offspring. DA in the optimal size of the offspring occurs only if partner quality affects the offspring benefit function. This is mostly in the form of greater female investment per offspring as male quality decreases. Simultaneously, we find that adaptive DA increases the number of offspring, and thus the amount of total investment, as male quality increases. Only certain model scenarios produce the positive DA in offspring size seen in empirical studies, providing a predictive framework for DA and how partner quality affects reproductive costs and offspring benefits.

Characteristics determining host suitability for a generalist parasite.

Host quality is critical for parasites. The common cuckoo Cuculus canorus is a generalist avian brood parasite, but individual females show strong preference for a specific host species. Here, we use three extensive datasets to investigate different host characteristics determining cuckoo host selection at the species level: (i) 1871 population-specific parasitism rates collected across Europe; (ii) 14 K cases of parasitism in the United Kingdom; and (iii) 16 K cases of parasitism in Germany, with data collected during the period 1735-2013. We find highly consistent effects of the different host species traits across our three datasets: the cuckoo prefers passerine host species of intermediate size that breed in grass- or shrubland and that feed their nestlings with insects, and avoids species that nest in cavities. Based on these results, we construct a novel host suitability index for all passerine species breeding in Europe, and show that host species known to have a corresponding cuckoo host race (gens) rank among the most suitable hosts in Europe. The distribution of our suitability index shows that host species cannot be classified as suitable or not but rather range within a continuum of suitability.

Differential Allocation Revisited: When Should Mate Quality Affect Parental Investment?

Differential allocation (DA) is the adaptive adjustment of reproductive investment (up or down) according to partner quality. A lack of theoretical treatments has led to some confusion in the interpretation of DA in the empirical literature. We present a formal framework for DA that highlights the nature of reproductive benefits versus costs for females mated to males of different quality. Contrary to popular belief, analytical and stochastic dynamic models both show that additive benefits of male quality on offspring fitness have no effect on optimal levels of female investment and thus cannot produce DA. Instead, if offspring fitness is affected multiplicatively by male quality, or male quality affects the female cost function, DA is expected because of changes in the marginal benefits or costs of extra investment. Additive male quality effects on the female cost function can cause a novel form of weak DA, because reduced costs can slightly favor current over future reproduction. Combinations of these distinct effects in more realistic model scenarios can explain various patterns of positive and negative DA reported for different species and mating systems. Our model therefore sheds new light on the diversity of empirical results by providing a strong conceptual framework for the DA hypothesis.

Sex ratio and density affect sexual selection in a sex-role reversed fish.

Understanding how demographic processes influence mating systems is important to decode ecological influences on sexual selection in nature. We manipulated sex ratio and density in experimental populations of the sex-role reversed pipefish Syngnathus typhle. We quantified sexual selection using the Bateman gradient (ßss'), the opportunity for selection (I), and sexual selection (Is), and the maximum standardized sexual selection differential (smax'). We also measured selection on body length using standardized selection differentials (s') and mating differentials (m'), and tested whether the observed I and Is differ from values obtained by simulating random mating. We found that I, Is, and s'max, but not ßss', were higher for females under female than male bias and the opposite for males, but density did not affect these measures. However, higher density decreased sexual selection (m' but not s') on female length, but selection on body length was not affected by sex ratio. Finally, Is but not I was higher than expected from random mating, and only for females under female bias. This study demonstrates that both sex ratio and density affect sexual selection and that disentangling interrelated demographic processes is essential to a more complete understanding of mating behavior and the evolution of mating systems.

Inertia: the discrepancy between individual and common good in dispersal and prospecting behaviour.

The group selection debate of the 1960s made it clear that evolution does not necessarily increase population performance. Individuals can be selected to have traits that diminish a common good and make population persistence difficult. At the extreme, the discrepancy between levels of selection is predicted to make traits evolve towards values at which a population can no longer persist (evolutionary suicide). Dispersal and prospecting are prime examples of traits that have a strong influence on population persistence under environmental and demographic stochasticity. Theory predicts that an 'optimal' dispersal strategy from a population point of view can differ considerably from that produced by individual-level selection. Because dispersal is frequently risky or otherwise costly, individuals are often predicted to disperse less than would be ideal for population performance (persistence or size). We define this discrepancy as 'inertia' and examine current knowledge of its occurrence and effects on population dynamics in nature. We argue that inertia is potentially widespread but that a framework is currently lacking for predicting precisely the extent to which it has a real influence on population persistence. The opposite of inertia, 'hypermobility' (more dispersal by individuals than would maximize population performance) remains a possibility: it is known that highest dispersal rates do not lead to best expected population performance, and examples of such high dispersal evolving exist at least in the theoretical literature. We also show, by considering prospecting behaviour, that similar issues arise in species with advanced cognitive and learning abilities. Individual prospecting strategies and the information acquired during dispersal are known to influence the decisions and therefore the fate of individuals and, as a corollary, populations. Again, the willingness of individuals to sample environments might evolve to levels that are not optimal for populations. This conflict can take intriguing forms. For example, better cognitive abilities of individuals may not always lead to better population-level performance. Simulation studies have found that 'blind' dispersal can lead to better connected metapopulations than cognitively more advanced habitat choice rules: the latter can lead to too many individuals sticking to nearby safe habitat. The study of the mismatch between individual and population fitness should not be a mere intellectual exercise. Population managers typically need to take a population-level view of performance, which may necessitate human intervention if it differs from what is selected for. We conclude that our knowledge of inertia and hypermobility would advance faster if theoretical studies--without much additional effort--quantified the population consequences of the evolving traits and compared this with hypothetical (not selectively favoured) dispersal rules, and if empirical studies were similarly conducted with the differing levels of selection in mind.

When density dependence is not instantaneous: theoretical developments and management implications.

Most organisms live in changing environments or do not use the same resources at different stages of their lives or in different seasons. As a result, density dependence will affect populations differently at different times. Such sequential density dependence generates markedly different population responses compared to the unrealistic assumption that all events occur simultaneously. Various field studies have also shown that the conditions that individuals experience during one period can influence success and per capita vital rates during the following period. These carry-over effects further complicate any general principles and increase the diversity of possible population dynamics. In this review, we describe how studies of sequential density dependence have diverged in directions that are both taxon-specific and have non-overlapping terminology, despite very similar underlying problems. By exploring and highlighting these similarities, we aim to improve communication between fields, clarify common misunderstandings, and provide a framework for improving conservation and management practices, including sustainable harvesting theory.