Gustavo S. Betini

The relationship between personality and plasticity in tree swallow aggression and the consequences for reproductive success

Both personality and plasticity can influence fitness, but few studies have investigated these two sources of individual variation simultaneously for the same behaviour. The individual quality hypothesis proposes that individuals with high personality scores will also be better able to respond to the changes in the environment (i.e. have a high degree of plasticity). Alternatively, the ‘compensatory’ hypothesis proposes that personality and plasticity are negatively correlated, because only individuals with low personality scores need to be able to rapidly adjust to environmental conditions. To examine these two hypotheses, we investigated the overall level of aggressiveness (personality) in nest defence, the ability of individuals to adjust this behaviour to respond to changes in temperature (plasticity), and their consequences for reproductive success in male and female tree swallows, Tachycineta bicolor. Using linear mixed effect models with individual as a random effect, we found that consistent differences between individuals explained approximately 55% of variation in aggressiveness and that more aggressive individuals were better able to adjust to variation in temperature, providing support for the individual quality hypothesis. However, although more aggressive males tended to fledge a higher number of young, the degree of plasticity only conferred a reproductive advantage for nonaggressive males, providing support for the compensatory hypothesis. For females, neither personality, nor plasticity was a good predictor of reproductive success. Our results suggest that personality and plasticity in aggressiveness are important components of individual variation but that the fitness advantages of each are context dependent.

Carry-over effects, sequential density dependence and the dynamics of populations in a seasonal environment

Most animal populations have distinct breeding and non-breeding periods, yet the implications of seasonality on population dynamics are not well understood. Here, we introduce an experimental model system to study the population dynamics of two important consequences of seasonality: sequential density dependence and carry-over effects (COEs). Using a replicated seasonal population of Drosophila, we placed individuals at four densities in the non-breeding season and then, among those that survived, placed them to breed at three different densities. We show that COEs arising from variation in non-breeding density negatively impacts individual performance by reducing per capita breeding output by 29–77%, implying that non-lethal COEs can have a strong influence on population abundance. We then parametrized a bi-seasonal population model from the experimental results, and show that both sequential density dependence and COEs can stabilize long-term population dynamics and that COEs can reduce population size at low intrinsic rates of growth. Our results have important implications for predicting the successful colonization of new habitats, and for understanding the long-term persistence of seasonal populations in a wide range of taxa, including migratory organisms.

Experimental evidence for the effect of habitat loss on the dynamics of migratory networks

Migratory animals present a unique challenge for understanding the consequences of habitat loss on population dynamics because individuals are typically distributed over a series of interconnected breeding and non-breeding sites (termed migratory network). Using replicated breeding and non-breeding populations of Drosophila melanogaster and a mathematical model, we investigated three hypotheses to explain how habitat loss influenced the dynamics of populations in networks with different degrees of connectivity between breeding and non-breeding seasons. We found that habitat loss increased the degree of connectivity in the network and influenced population size at sites that were not directly connected to the site where habitat loss occurred. However, connected networks only buffered global population declines at high levels of habitat loss. Our results demonstrate why knowledge of the patterns of connectivity across a species range is critical for predicting the effects of environmental change and provide empirical evidence for why connected migratory networks are commonly found in nature.

Body size, carry‐over effects and survival in a seasonal environment: consequences for population dynamics

In seasonal populations, vital rates are not only determined by the direct effects of density at the beginning of each season, but also by density at the beginning of past seasons. Such delayed density dependence can arise via non-lethal effects on individuals that carry over to influence per capita rates. In this study, we examine (i) whether parental breeding density influences offspring size, (ii) how this could carry over to affect offspring survival during the subsequent non-breeding period and (iii) the population consequences of this relationship. Using Drosophila melanogaster, the common fruit fly, submitted to distinct breeding and non-breeding seasons, we first used a controlled laboratory experiment to show that high parental breeding density leads to small offspring size, which then affects offspring survival during the non-breeding period but only at high non-breeding densities. We then show that a model with the interaction between parental breeding density and offspring density at the beginning of the non-breeding season best explained offspring survival over 36 replicated generations. Finally, we developed a biseasonal model to show that the positive relationship between parental density and offspring survival can dampen fluctuations in population size between breeding and non-breeding seasons. These results highlight how variation in parental density can lead to differences in offspring quality which result in important non-lethal effects that carry over to influence per capita rates the following season, and demonstrate how this phenomenon can have important implications for the long-term dynamics of seasonal populations.

Experimental evidence for within‐ and cross‐seasonal effects of fear on survival and reproduction

Fear of predation can have non-lethal effects on individuals within a season but whether, and to what extent, these effects carry over into subsequent seasons is not known. Using a replicated seasonal population of the common fruit fly, Drosophila melanogaster, we examined both within- and cross-seasonal effects of fear on survival and reproductive output. Compared to controls, flies exposed to the scent of mantid (Tenodera sinensis) predators in the non-breeding season had 64% higher mortality, and lost 60% more mass by the end of the non-breeding season and, in the subsequent breeding season, produced 20% fewer offspring that weighed 9% less at maturity. Flies exposed to the scent of mantids in the breeding season did not produce fewer offspring, but their offspring developed faster and weighed less as adults compared to the controls. Our results demonstrate how effects of fear can be manifested both within and across seasons and emphasize the importance of understanding how events throughout the annual cycle influence individual success of animals living in seasonal environments.

Density-mediated carry-over effects explain variation in breeding output across time in a seasonal population

In seasonal environments, where density dependence can operate throughout the annual cycle, vital rates are typically considered to be a function of the number of individuals at the beginning of each season. However, variation in density in the previous season could also cause surviving individuals to be in poor physiological condition, which could carry over to influence individual success in the following season. We examine this hypothesis using replicated populations of Drosophila melanogaster, the common fruitfly, over 23 non-overlapping generations with distinct breeding and non-breeding seasons. We found that the density at the beginning of the non-breeding season negatively affected the fresh weight of individuals that survived the non-breeding season and resulted in a 25% decrease in per capita breeding output among those that survived to the next season to breed. At the population level, per capita breeding output was best explained by a model that incorporated density at the beginning of the previous non-breeding season (carry-over effect, COE) and density at the beginning of the breeding season. Our results support the idea that density-mediated COEs are critical for understanding population dynamics in seasonal environments.

Understanding Evolutionary Impacts of Seasonality: An Introduction to the Symposium

Seasonality is a critically important aspect of environmental variability, and strongly shapes all aspects of life for organisms living in highly seasonal environments. Seasonality has played a key role in generating biodiversity, and has driven the evolution of extreme physiological adaptations and behaviors such as migration and hibernation. Fluctuating selection pressures on survival and fecundity between summer and winter provide a complex selective landscape, which can be met by a combination of three outcomes of adaptive evolution: genetic polymorphism, phenotypic plasticity, and bet-hedging. Here, we have identified four important research questions with the goal of advancing our understanding of evolutionary impacts of seasonality. First, we ask how characteristics of environments and species will determine which adaptive response occurs. Relevant characteristics include costs and limits of plasticity, predictability, and reliability of cues, and grain of environmental variation relative to generation time. A second important question is how phenological shifts will amplify or ameliorate selection on physiological hardiness. Shifts in phenology can preserve the thermal niche despite shifts in climate, but may fail to completely conserve the niche or may even expose life stages to conditions that cause mortality. Considering distinct environmental sensitivities of life history stages will be key to refining models that forecast susceptibility to climate change. Third, we must identify critical physiological phenotypes that underlie seasonal adaptation and work toward understanding the genetic architectures of these responses. These architectures are key for predicting evolutionary responses. Pleiotropic genes that regulate multiple responses to changing seasons may facilitate coordination among functionally related traits, or conversely may constrain the expression of optimal phenotypes. Finally, we must advance our understanding of how changes in seasonal fluctuations are impacting ecological interaction networks. We should move beyond simple dyadic interactions, such as predator prey dynamics, and understand how these interactions scale up to affect ecological interaction networks. As global climate change alters many aspects of seasonal variability, including extreme events and changes in mean conditions, organisms must respond appropriately or go extinct. The outcome of adaptation to seasonality will determine responses to climate change.

A fitness trade-off between seasons causes multigenerational cycles in phenotype and population size

Although seasonality is widespread and can cause fluctuations in the intensity and direction of natural selection, we have little information about the consequences of seasonal fitness trade-offs for population dynamics. Here we exposed populations of Drosophila melanogaster to repeated seasonal changes in resources across 58 generations and used experimental and mathematical approaches to investigate how viability selection on body size in the non-breeding season could affect demography. We show that opposing seasonal episodes of natural selection on body size interacted with both direct and delayed density dependence to cause populations to undergo predictable multigenerational density cycles. Our results provide evidence that seasonality can set the conditions for life-history trade-offs and density dependence, which can, in turn, interact to cause multigenerational population cycles. DOI: http://dx.doi.org/10.7554/eLife.18770.001

Why are we not evaluating multiple competing hypotheses in ecology and evolution

The use of multiple working hypotheses to gain strong inference is widely promoted as a means to enhance the effectiveness of scientific investigation. Only 21 of 100 randomly selected studies from the ecological and evolutionary literature tested more than one hypothesis and only eight tested more than two hypotheses. The surprising rarity of application of multiple working hypotheses suggests that this gap between theory and practice might reflect some fundamental issues. Here, we identify several intellectual and practical barriers that discourage us from using multiple hypotheses in our scientific investigation. While scientists have developed a number of ways to avoid biases, such as the use of double-blind controls, we suspect that few scientists are fully aware of the potential influence of cognitive bias on their decisions and they have not yet adopted many techniques available to overcome intellectual and practical barriers in order to improve scientific investigation.

The role of seasonality and non-lethal carry-over effects on density-dependent dispersal

Understanding dispersal is critical for predicting a wide range of ecological dynamics. Variation in intraspecific density is widely regarded as a major factor influencing dispersal rates but it is not clear why dispersal is positively related to density in some systems and negatively related to density in other systems. Using seasonal populations of Drosophila melanogaster, we experimentally show that dispersal rates are both positively related to breeding density at the time of dispersal and negatively related to density at the beginning of the previous non-breeding season. This suggests that flies use density at the time of dispersal as a cue for habitat quality but are also negatively influenced by the delayed, non-lethal effects of density in the previous season. A parameterized model indicates that a carry-over effect not only causes a decrease in the proportion of individuals that disperse, but also a decrease in population size caused by lower per capita breeding output. Our results demonstrate how density can have contrasting effects on dispersal and population size depending on when density is measured in the annual cycle and that non-lethal effects on individuals can have important, but previously unrecognized, consequences for both the movement rates and long-term dynamics of seasonal populations.