Does Reproductive Investment Decrease Telomere Length in Menidia menidia?

Given finite resources, intense investment in one life history trait is expected to reduce investment in others. Although telomere length appears to be strongly tied to age in many taxa, telomere maintenance requires energy. We therefore hypothesize that telomere maintenance may trade off against other life history characters. We used natural variation in laboratory populations of Atlantic silversides (Menidia menidia) to study the relationship between growth, fecundity, life expectancy, and relative telomere length. In keeping with several other studies on fishes, we found no clear dependence of telomere length on age. However, we did find that more fecund fish tended to have both reduced life expectancy and shorter telomeres. This result is consistent with the hypothesis that there is a trade-off between telomere maintenance and reproductive output

Constraining nonlinear time series modeling with the metabolic theory of ecology

Forecasting the response of ecological systems to environmental change is a critical challenge for sustainable management. The metabolic theory of ecology (MTE) posits scaling of biological rates with temperature, but it has had limited application to population dynamic forecasting. Here we use the temperature dependence of the MTE to constrain empirical dynamic modeling (EDM), an equation-free nonlinear machine learning approach for forecasting. By rescaling time with temperature and modeling dynamics on a “metabolic time step,” our method (MTE-EDM) improved forecast accuracy in 18 of 19 empirical ectotherm time series (by 19% on average), with the largest gains in more seasonal environments. MTE-EDM assumes that temperature affects only the rate, rather than the form, of population dynamics, and that interacting species have approximately similar temperature dependence. A review of laboratory studies suggests these assumptions are reasonable, at least approximately, though not for all ecological systems. Our approach highlights how to combine modern data-driven forecasting techniques with ecological theory and mechanistic understanding to predict the response of complex ecosystems to temperature variability and trends

Thermal transgenerational effects remain after two generations

Transgenerational plasticity (TGP) is increasingly recognized as a mechanism by which organisms can respond to environments that change across generations. Although recent empirical and theoretical studies have explored conditions under which TGP is predicted to evolve, it is still unclear whether the effects of the parental environment will remain beyond the offspring generation. Using a small cyprinodontid fish, we explored multigenerational thermal TGP to address two related questions. First (experiment 1), does the strength of TGP decline or accumulate across multiple generations? Second (experiment 2), how does the experience of a temperature novel to both parents and offspring affect the strength of TGP? In the first experiment, we found a significant interaction between F1 and F2 temperatures and juvenile growth, but no effect of egg diameter. The strength of TGP between F0 and F1 generations was similar in both experiments but declined in subsequent generations. Further, experience of a novel temperature accelerated the decline. This pattern, although similar to that found in other species, is certainly not universally observed, suggesting that theoretical and empirical effort is needed to understand the multigenerational dynamics of TGP.publishedVersio

Thermal reaction norms for growth vary among cohorts of Pacific cod (Gadus macrocephalus)

While much effort has been directed at determining the spatial scales of adaptation in thermal reaction norms for growth, it is widely assumed that these reaction norms have high temporal stability. Water temperatures in the Gulf of Alaska in 2007 were the coldest on record since the mid-1970s and we present evidence that the thermal reaction norm for growth of age-0 Pacific cod (Gadus macrocephalus) in this cohort differed significantly from two adjacent cohorts. In addition to exhibiting higher growth potential at low temperatures, the 2007 cohort had a higher mean vertebral count, consistent with the widespread thermal effect known as “Jordan’s Rule.” Variation among cohorts in these physiological and morphological traits suggests a persistent response to environmental history (epigenetic effect). Temperature-induced phenotypic plasticity in the reaction norm for growth has significant implications for using growth rates to evaluate habitat quality and illustrates the complex responses of fishes to climate variability

The relationship between maternal phenotype and offspring quality: Do older mothers really produce the best offspring?

Maternal effects are increasingly recognized as important drivers of population dynamics and determinants of evolutionary trajectories. Recently, there has been a proliferation of studies finding or citing a positive relationship between maternal size/age and offspring size or offspring quality. The relationship between maternal phenotype and offspring size is intriguing in that it is unclear why young mothers should produce offspring of inferior quality or fitness. Here we evaluate the underlying evolutionary pressures that may lead to a maternal size/age-offspring size correlation and consider the likelihood that such a correlation results in a positive relationship between the age or size of mothers and the fitness of their offspring. We find that, while there are a number of reasons why selection may favor the production of larger offspring by larger mothers, this change in size is more likely due to associated changes in the maternal phenotype that affect the offspring size-performance relationship. We did not find evidence that the offspring of older females should have intrinsically higher fitness. When we explored this issue theoretically, the only instance in which smaller mothers produce suboptimal offspring sizes is when a (largely unsupported) constraint on maximum offspring size is introduced into the model. It is clear that larger offspring fare better than smaller offspring when reared in the same environment, but this misses a critical point: different environments elicit selection for different optimal sizes of young. We suggest that caution should be exercised when interpreting the outcome of offspring-size experiments when offspring from different mothers are reared in a common environment, because this approach may remove the source of selection (e.g., reproducing in different context) that induced a shift in offspring size in the first place. It has been suggested that fish stocks should be managed to preserve these older age classes because larger mothers produce offspring with a greater chance of survival and subsequent recruitment. Overall, we suggest that, while there are clear and compelling reasons for preserving older females in exploited populations, there is little theoretical justification or evidence that older mothers produce offspring with higher per capita fitness than do younger mothers

High connectivity among locally adapted populations of a marine fish (Menidia menidia)

Author Posting. © Ecological Society of America, 2010. This article is posted here by permission of Ecological Society of America for personal use, not for redistribution. The definitive version was published in Ecology 91 (2010): 3526–3537, doi:10.1890/09-0548.1.Patterns of connectivity are important in understanding the geographic scale of local adaptation in marine populations. While natural selection can lead to local adaptation, high connectivity can diminish the potential for such adaptation to occur. Connectivity, defined as the exchange of individuals among subpopulations, is presumed to be significant in most marine species due to life histories that include widely dispersive stages. However, evidence of local adaptation in marine species, such the Atlantic silverside, Menidia menidia, raises questions concerning the degree of connectivity. We examined geochemical signatures in the otoliths, or ear bones, of adult Atlantic silversides collected in 11 locations along the northeastern coast of the United States from New Jersey to Maine in 2004 and eight locations in 2005 using laser ablation inductively coupled plasma mass spectrometry (ICP-MS) and isotope ratio monitoring mass spectrometry (irm-MS). These signatures were then compared to baseline signatures of juvenile fish of known origin to determine natal origin of these adult fish. We then estimated migration distances and the degree of mixing from these data. In both years, fish generally had the highest probability of originating from the same location in which they were captured (0.01–0.80), but evidence of mixing throughout the sample area was present. Furthermore, adult M. menidia exhibit highly dispersive behavior with some fish migrating over 700 km. The probability of adult fish returning to natal areas differed between years, with the probability being, on average, 0.2 higher in the second year. These findings demonstrate that marine species with largely open populations are capable of local adaptation despite apparently high gene flow.This work was funded by the National Science Foundation (grant OCE-0425830 to D. O. Conover and grant OCE- 0134998 to S. R. Thorrold) and the New York State Department of Environmental Conservation

The intrinsic predictability of ecological time series and its potential to guide forecasting

Successfully predicting the future states of systems that are complex, stochastic, and potentially chaotic is a major challenge. Model forecasting error (FE) is the usual measure of success; however model predictions provide no insights into the potential for improvement. In short, the realized predictability of a specific model is uninformative about whether the system is inherently predictable or whether the chosen model is a poor match for the system and our observations thereof. Ideally, model proficiency would be judged with respect to the systems’ intrinsic predictability, the highest achievable predictability given the degree to which system dynamics are the result of deterministic vs. stochastic processes. Intrinsic predictability may be quantified with permutation entropy (PE), a model‐free, information‐theoretic measure of the complexity of a time series. By means of simulations, we show that a correlation exists between estimated PE and FE and show how stochasticity, process error, and chaotic dynamics affect the relationship. This relationship is verified for a data set of 461 empirical ecological time series. We show how deviations from the expected PE–FE relationship are related to covariates of data quality and the nonlinearity of ecological dynamics. These results demonstrate a theoretically grounded basis for a model‐free evaluation of a system's intrinsic predictability. Identifying the gap between the intrinsic and realized predictability of time series will enable researchers to understand whether forecasting proficiency is limited by the quality and quantity of their data or the ability of the chosen forecasting model to explain the data. Intrinsic predictability also provides a model‐free baseline of forecasting proficiency against which modeling efforts can be evaluated

Environmental variability and fishing effects on the Pacific sardine fisheries in the Gulf of California

Small pelagic fish support some of the largest fisheries globally, yet there is an ongoing debate about the magnitude of the impacts of environmental processes and fishing activities on target species. We use a nonparametric, nonlinear approach to quantify these effects on the Pacific sardine (Sardinops sagax) in the Gulf of California. We show that the effect of fishing pressure and environmental variability are comparable. Furthermore, when predicting total catches, the best models account for both drivers. By using empirical dynamic programming with average environmental conditions, we calculated optimal policies to ensure long-term sustainable fisheries. The first policy, the equilibrium maximum sustainable yield, suggests that the fishery could sustain an annual catch of ∼2.16 × 105 tonnes. The second policy with dynamic optimal effort, reveals that the effort from 2 to 4 years ago impacts the current maximum sustainable effort. Consecutive years of high effort require a reduction to let the stock recover. Our work highlights a new framework that embraces the complex processes that drive fisheries population dynamics yet produces simple and robust advice to ensure long-term sustainable fisheries.Published versio

Circularity in fisheries data weakens real world prediction

The systematic substitution of direct observational data with synthesized data derived from models during the stock assessment process has emerged as a low-cost alternative to direct data collection efforts. What is not widely appreciated, however, is how the use of such synthesized data can overestimate predictive skill when forecasting recruitment is part of the assessment process. Using a global database of stock assessments, we show that Standard Fisheries Models (SFMs) can successfully predict synthesized data based on presumed stock-recruitment relationships, however, they are generally less skillful at predicting observational data that are either raw or minimally filtered (denoised without using explicit stock-recruitment models). Additionally, we find that an equation-free approach that does not presume a specific stock-recruitment relationship is better than SFMs at predicting synthesized data, and moreover it can also predict observational recruitment data very well. Thus, while synthesized datasets are cheaper in the short term, they carry costs that can limit their utility in predicting real world recruitment.https://www.nature.com/articles/s41598-020-63773-3Published versio