Beyond the single biggest fish: robust inference of species maximum length (Lmax) from sample maxima - Freddie Heather; Stephan Munch; Asta Audzijonyte (Reviews in Fish Biology and Fisheries, 2026)
1. Maximum body length ( $${L}_{max}$$ L max ) is a key trait for describing an animal species’ biological characteristics, ecology, and vulnerability to exploitation. This is particularly true for fish species, and $${L}_{max}$$ L max is widely used in fisheries and is a key parameter in population assessments. Yet $${L}_{max}$$ L max estimation is strongly contingent on sampling intensity, and uncertainty is rarely quantified or propagated in downstream applications. 2. We apply and develop two complementary estimators of $${L}_{max}$$ L max and its uncertainty using observations of the largest individuals recorded across multiple samples of approximately similar size. First, using Extreme Value Theory (EVT), a method widely used in insurance and finance, we use the Generalised Extreme Value distribution to model the probability of an extreme event, i.e., the observation of a certain individual body length. Second, we propose a new method, an Exact Finite Sample (EFS) approach, which estimates the most likely parameters of the underlying body‐size distribution that gives rise to the observed sample maxima. We use Bayesian inference for both methods to estimate the expected maximum individual body length for a given sampling effort (e.g., the expected maximum from 20 comparable samples) with credible intervals. 3. Sensitivity analyses show that both EVT and EFS recover unbiased $${L}_{max}$$ L max when samples arise from approximately truncated-normal population length-frequency distributions. For heavier right-tailed length-frequency distributions, both methods tend to underestimate $${L}_{max}$$ L max (5–15%), with EVT yielding wider uncertainty but less sensitivity to distribution misspecification. For animal, and especially fish, ecology and management applications, we recommend reporting a “20-sample maximum $${L}_{max}$$ L max ”, defined as the 95th percentile of the probability density function of the maximum lengths, as a practical benchmark that is comparable across studies and explicitly conditions on sampling effort. As a case-study, we use 14 fishing competition records for Australasian snapper ( Chrysophrys auratus ) and estimate its 20-sample $${L}_{max}$$ L max as 139 cm (127–151 cm, 80% credible interval) using EVT, and 126 cm (121–133 cm, 80% credible interval) using EFS.

A Nonequilibrium Framework for Community Responses to Pulse Perturbations - Lucas P. Medeiros; Michael G. Neubert; Heidi M. Sosik; Stephan B. Munch (Ecology Letters, 2026)
Understanding responses of ecological communities to shocks that displace species abundances is of paramount importance given the increasing frequency of extreme climatic events. However, current theory on responses to such pulse perturbations focuses on equilibrium points and we lack a unified framework that accommodates other common, but more complicated, population fluctuations such as transients and cycles. Here we introduce this framework by deriving metrics that quantify the minimum, typical and maximum amplification of perturbed abundances for nonequilibrium population dynamics. By simulating models under several nonequilibrium scenarios, we demonstrate that these metrics accurately characterise the full range of amplification of perturbed abundances in the short and long terms. Notably, we show that perturbation amplification depends strongly on community state in the short term, but this state dependency vanishes in the long term. We illustrate how our framework can provide insights about models and data for communities that are not at equilibrium.

Empirical dynamic modeling for prediction and control of pest populations - Bethany J. Johnson; Marcella M. Gomez; Stephan B. Munch (Ecological Modelling, 2025)

Predicting spring phenology in deciduous broadleaf forests: NEON phenology forecasting community challenge - Kathryn I. Wheeler; Michael C. Dietze; David LeBauer; Jody A. Peters; Andrew D. Richardson; Arun A. Ross; R. Quinn Thomas; Kai Zhu; Uttam Bhat; Stephan Munch; Raphaela Floreani Buzbee; Min Chen; et al. (Agricultural and Forest Meteorology, 2024)

Effects of daily thermal fluctuations on the Atlantic silverside, a fish with temperature‐dependent sex determination - Grace M. Hancock; Gorka Sancho; Stephan B. Munch; Santiago Salinas (Journal of Fish Biology, 2023)
Temperature‐dependent sex determination (TSD) occurs when the temperature during development affects gonad determination. Historically, most work on TSD in fishes was conducted under constant temperatures, yet daily fluctuating temperatures can significantly alter fish physiology and life history. Thus, we subjected the Atlantic silverside, Menidia menidia (a TSD species), to 28, 28 ± 2 and 28 ± 4°C (a high, masculinizing temperature) and quantified sex ratios and length. We found that the percentage of females increased by 60%–70% when the fish were exposed to daily fluctuating temperatures (from 10% to 16% and 17% under fluctuations).

Intermittent instability is widespread in plankton communities - Tanya L. Rogers; Stephan B. Munch; Shin‐ichiro S. Matsuzaki; Celia C. Symons (Ecology Letters, 2023)
Chaotic dynamics appear to be prevalent in short‐lived organisms including plankton and may limit long‐term predictability. However, few studies have explored how dynamical stability varies through time, across space and at different taxonomic resolutions. Using plankton time series data from 17 lakes and 4 marine sites, we found seasonal patterns of local instability in many species, that short‐term predictability was related to local instability, and that local instability occurred most often in the spring, associated with periods of high growth. Taxonomic aggregates were more stable and more predictable than finer groupings. Across sites, higher latitude locations had higher Lyapunov exponents and greater seasonality in local instability, but only at coarser taxonomic resolution. Overall, these results suggest that prediction accuracy, sensitivity to change and management efficacy may be greater at certain times of year and that prediction will be more feasible for taxonomic aggregates.

Forecasting in the face of ecological complexity: Number and strength of species interactions determine forecast skill in ecological communities - Uriah Daugaard; Stephan B. Munch; David Inauen; Frank Pennekamp; Owen L. Petchey (Ecology Letters, 2022)
The potential for forecasting the dynamics of ecological systems is currently unclear, with contrasting opinions regarding its feasibility due to ecological complexity. To investigate forecast skill within and across systems, we monitored a microbial system exposed to either constant or fluctuating temperatures in a 5‐month‐long laboratory experiment. We tested how forecasting of species abundances depends on the number and strength of interactions and on model size (number of predictors). We also tested how greater system complexity (i.e. the fluctuating temperatures) impacted these relations. We found that the more interactions a species had, the weaker these interactions were and the better its abundance was predicted. Forecast skill increased with model size. Greater system complexity decreased forecast skill for three out of eight species. These insights into how abundance prediction depends on the connectedness of the species within the system and on overall system complexity could improve species forecasting and monitoring.

Applying empirical dynamic modeling to distinguish abiotic and biotic drivers of population fluctuations in sympatric fishes - Ben A. Wasserman; Tanya L. Rogers; Stephan B. Munch; Eric P. Palkovacs (Limnology and Oceanography, 2022)
Fluctuations in the population abundances of interacting species are widespread. Such fluctuations could be a response to abiotic factors, biotic interactions, or a combination of the two. Correctly identifying the drivers is critical for effective population management. However, such effects are not always static in nature. Nonlinear relationships between abiotic factors and biotic interactions make it difficult to parse true effects. We used a type of nonlinear forecasting, empirical dynamic modeling, to investigate the context‐dependent species interaction between a common fish (three‐spine stickleback) and an endangered one (northern tidewater goby) in a fluctuating environment: a central California bar‐built estuary. We found little evidence for competition, instead both species largely responded independently to abiotic conditions. Stickleback were negatively affected by sandbar breaching. The strongest predictor of tidewater goby abundance was stickleback abundance; however, this effect was not a uniform negative effect of stickleback on goby as would be hypothesized under interspecific competition. The effect of stickleback on gobies was positive, though it was temporally restricted. Tidewater goby abundance in the summer was strongly positively correlated to stickleback abundance in the spring, which represents an offset in the reproductive and recruitment peaks in the two species that may help minimize competition and promote coexistence. Our study demonstrates how empirical dynamic modeling can be applied to understand drivers of population abundance in putative competitors and inform management for endangered species.

Separating Paternal and Maternal Contributions to Thermal Transgenerational Plasticity - Sarah L. Chang; Who-Seung Lee; Stephan B. Munch (Frontiers in Marine Science, 2021)
Climate change is rapidly altering the thermal environment in terrestrial and aquatic systems. Transgenerational thermal plasticity (TGP) – which occurs when the temperatures experienced by the parental generation prior to the fertilization of gametes results in a change in offspring reaction norms – may mitigate the effects of climate change. Although “maternal effects” have been widely studied, relatively little is known about TGP effects in vertebrates, particularly paternal contributions. We used artificial fertilization to cross sheepshead minnow ( Cyprinodon variegatus ) parents exposed to either low (26°C) or high (32°C) temperatures and measured growth rates of the offspring over the first 8 weeks of life at both low and high temperatures. A linear mixed effects model was employed to quantify the effects of maternal, paternal, and offspring temperatures on offspring growth and fecundity. We found that the offspring growth rate up to 63 days post-hatch was affected by both the temperature they experienced directly and parental temperatures prior to fertilization. Growth was lowest when neither parents’ temperature matched the offspring temperature, indicating a strong transgenerational effect. Notably, offspring growth was highest when all three (offspring, sire, and dam) temperatures matched [although the three-way interaction was found to be marginally non-significant ( P = 0.155)], suggesting that TGP effects were additive across significant sire-offspring ( P < 0.001) and dam-offspring interactions ( P < 0.001). Transgenerational effects on fecundity (GSI) were suggestive for both maternal and paternal effects, but not significant. The finding that thermal TGP is contributed by both parents strongly suggests that it has an epigenetic basis.

Trophic control changes with season and nutrient loading in lakes - Tanya L. Rogers; Stephan B. Munch; Simon D. Stewart; Eric P. Palkovacs; Alfredo Giron‐Nava; Shin‐ichiro S. Matsuzaki; Celia C. Symons (Ecology Letters, 2020)
Experiments have revealed much about top‐down and bottom‐up control in ecosystems, but manipulative experiments are limited in spatial and temporal scale. To obtain a more nuanced understanding of trophic control over large scales, we explored long‐term time‐series data from 13 globally distributed lakes and used empirical dynamic modelling to quantify interaction strengths between zooplankton and phytoplankton over time within and across lakes. Across all lakes, top‐down effects were associated with nutrients, switching from negative in mesotrophic lakes to positive in oligotrophic lakes. This result suggests that zooplankton nutrient recycling exceeds grazing pressure in nutrient‐limited systems. Within individual lakes, results were consistent with a ‘seasonal reset’ hypothesis in which top‐down and bottom‐up interactions varied seasonally and were both strongest at the beginning of the growing season. Thus, trophic control is not static, but varies with abiotic conditions – dynamics that only become evident when observing changes over large spatial and temporal scales.

Nonlinear dynamics and noise in fisheries recruitment: A global meta‐analysis - Stephan B. Munch; Alfredo Giron‐Nava; George Sugihara (Fish and Fisheries, 2018)
The relative importance of environmental and intrinsic controls on recruitment in fishes has been studied for over a century. Despite this, we are not much closer to predicting recruitment. Rather, recent analyses suggest that recruitment is virtually independent of stock size and, instead, seems to occur in distinct environmental regimes. This issue of whether or not recruitment and subsequent production are coupled to stock size is highly relevant to management. Here, we apply empirical dynamical modelling ( EDM ) to a global database of 185 fish populations to address the questions of whether or not variation in recruitment is (a) predictable and (b) coupled to stock size. We find that a substantial fraction of recruitment variation is predictable using only the observed history of fluctuations (~40% on average). In addition, although recruitment is often coupled to stock size (107 of 185 stocks), stock size alone explains very little of the variation in recruitment; In ~90% of the stocks analysed, EDM forecasts have substantially lower prediction error than models based solely on stock size. We find that predictability varies across taxa and improves with the number of generations that have been sampled. In the light of these results, we suggest that EDM will be of greatest use in managing relatively short‐lived species.

Avoiding a crisis of motivation for ocean management under global environmental change - Peter J. Mumby; James N. Sanchirico; Kenneth Broad; Michael W. Beck; Peter Tyedmers; Megan Morikawa; Thomas A. Okey; Larry B. Crowder; Elizabeth A. Fulton; Denny Kelso; Joanie A. Kleypas; Stephan B. Munch; et al. (Global Change Biology, 2017)
Climate change and ocean acidification are altering marine ecosystems and, from a human perspective, creating both winners and losers. Human responses to these changes are complex, but may result in reduced government investments in regulation, resource management, monitoring and enforcement. Moreover, a lack of peoples’ experience of climate change may drive some towards attributing the symptoms of climate change to more familiar causes such as management failure. Taken together, we anticipate that management could become weaker and less effective as climate change continues. Using diverse case studies, including the decline of coral reefs, coastal defences from flooding, shifting fish stocks and the emergence of new shipping opportunities in the Arctic, we argue that human interests are better served by increased investments in resource management. But greater government investment in management does not simply mean more of “business‐as‐usual.” Management needs to become more flexible, better at anticipating and responding to surprise, and able to facilitate change where it is desirable. A range of technological, economic, communication and governance solutions exists to help transform management. While not all have been tested, judicious application of the most appropriate solutions should help humanity adapt to novel circumstances and seek opportunity where possible.

Combining functional data with hierarchical Gaussian process models - Valerie Poynor; Stephan Munch (Environmental and Ecological Statistics, 2017)

Estimating partial regulation in spatiotemporal models of community dynamics - James T. Thorson; Stephan B. Munch; Douglas P. Swain (Ecology, 2017)
Niche‐based approaches to community analysis often involve estimating a matrix of pairwise interactions among species (the “community matrix”), but this task becomes infeasible using observational data as the number of modeled species increases. As an alternative, neutral theories achieve parsimony by assuming that species within a trophic level are exchangeable, but generally cannot incorporate stabilizing interactions even when they are evident in field data. Finally, both regulated (niche) and unregulated (neutral) approaches have rarely been fitted directly to survey data using spatiotemporal statistical methods. We therefore propose a spatiotemporal and model‐based approach to estimate community dynamics that are partially regulated. Specifically, we start with a neutral spatiotemporal model where all species follow ecological drift, which precludes estimating pairwise interactions. We then add regulatory relations until model selection favors stopping, where the “rank” of the interaction matrix may range from zero to the number of species. A simulation experiment shows that model selection can accurately identify the rank of the interaction matrix, and that the identified spatiotemporal model can estimate the magnitude of species interactions. A 40‐yr case study for the Gulf of St. Lawrence marine community shows that recovering grey seals have an unregulated and negative relationship with demersal fishes. We therefore conclude that partial regulation is a plausible approximation to community dynamics using field data and hypothesize that estimating partial regulation will be expedient in future analyses of spatiotemporal community dynamics given limited field data. We conclude by recommending ongoing research to add explicit models for movement, so that meta‐community theory can be confronted with data in a spatiotemporal statistical framework.

Why do larger mothers produce larger offspring? A test of classic theory - Hayley Cameron; Keyne Monro; Martino Malerba; Stephan Munch; Dustin Marshall (Ecology, 2016)
Across a wide range of taxa, larger mothers produce larger offspring. Theory assumes that larger, more fecund mothers create higher local densities of siblings, and so larger mothers produce larger offspring to offset sibling competition. This assumption has been debated for over 30 yr, but direct empirical tests are surprisingly rare. Here, we test two key assumptions of classic theories that predict sibling competition drives maternal‐size–offspring‐size ( MSOS ) correlations: (1) independent effects of offspring size and sibling density on offspring performance or (2) as a product of an interaction between these two factors. To simultaneously test these alternative assumptions, we manipulate offspring size and sibling density in the marine invertebrate, Bugula neritina, and monitor offspring performance in the field. We found that depending on the fitness metric being considered, offspring size and sibling density can either independently or interactively affect offspring performance. Yet sibling density did not affect offspring performance in the ways that classic theories assume. Given our results, it is unlikely that sibling competition drives the positive MSOS correlation observed in this species. Empirical support for these classic theories remains lacking, suggesting alternative explanations are necessary.

The global contribution of forage fish to marine fisheries and ecosystems - Ellen K Pikitch; Konstantine J Rountos; Timothy E Essington; Christine Santora; Daniel Pauly; Reg Watson; Ussif R Sumaila; P Dee Boersma; Ian L Boyd; David O Conover; Philippe Cury; Selina S Heppell; et al. (Fish and Fisheries, 2014)
Forage fish play a pivotal role in marine ecosystems and economies worldwide by sustaining many predators and fisheries directly and indirectly. We estimate global forage fish contributions to marine ecosystems through a synthesis of 72 published E copath models from around the world. Three distinct contributions of forage fish were examined: (i) the ecological support service of forage fish to predators in marine ecosystems, (ii) the total catch and value of forage fisheries and (iii) the support service of forage fish to the catch and value of other commercially targeted predators. Forage fish use and value varied and exhibited patterns across latitudes and ecosystem types. Forage fish supported many kinds of predators, including fish, seabirds, marine mammals and squid. Overall, forage fish contribute a total of about $16.9 billion USD to global fisheries values annually, i.e. 20% of the global ex‐vessel catch values of all marine fisheries combined. While the global catch value of forage fisheries was $5.6 billion, fisheries supported by forage fish were more than twice as valuable ($11.3 billion). These estimates provide important information for evaluating the trade‐offs of various uses of forage fish across ecosystem types, latitudes and globally. We did not estimate a monetary value for supportive contributions of forage fish to recreational fisheries or to uses unrelated to fisheries, and thus the estimates of economic value reported herein understate the global value of forage fishes.

A Bayesian approach to identifying and compensating for model misspecification in population models - James T. Thorson; Kotaro Ono; Stephan B. Munch (Ecology, 2014)
State‐space estimation methods are increasingly used in ecology to estimate productivity and abundance of natural populations while accounting for variability in both population dynamics and measurement processes. However, functional forms for population dynamics and density dependence often will not match the true biological process, and this may degrade the performance of state‐space methods. We therefore developed a Bayesian semiparametric state‐space model, which uses a Gaussian process (GP) to approximate the population growth function. This offers two benefits for population modeling. First, it allows data to update a specified “prior” on the population growth function, while reverting to this prior when data are uninformative. Second, it allows variability in population dynamics to be decomposed into random errors around the population growth function (“process error”) and errors due to the mismatch between the specified prior and estimated growth function (“model error”). We used simulation modeling to illustrate the utility of GP methods in state‐space population dynamics models. Results confirmed that the GP model performs similarly to a conventional state‐space model when either (1) the prior matches the true process or (2) data are relatively uninformative. However, GP methods improve estimates of the population growth function when the function is misspecified. Results also demonstrated that the estimated magnitude of “model error” can be used to distinguish cases of model misspecification. We conclude with a discussion of the prospects for GP methods in other state‐space models, including age and length‐structured, meta‐analytic, and individual‐movement models.

A semiparametric Bayesian method for detecting Allee effects - Masatoshi Sugeno; Stephan B Munch (Ecology, 2013)
The importance of Allee effects has long been recognized both in theoretical studies of population dynamics and in conservation sciences. Although the necessary conditions for Allee effects to occur (e.g., difficulty in finding mates and mortality driven by generalist predators at low density) would seem to apply to many species, evidence for Allee effects in natural populations is equivocal at best. This apparent scarcity might be an artifact driven by poor power to detect them with traditional parametric models. To circumvent this potential problem, we developed a semiparametric Bayesian method based on a Gaussian process prior. We validated the method using simulated data sets and applied it to three herring data sets.

Nonparametric forecasting outperforms parametric methods for a simulated multispecies system - Charles T. Perretti; George Sugihara; Stephan B. Munch (Ecology, 2013)
Ecosystem dynamics are often complex, nonlinear, and characterized by critical thresholds or phase shifts. To implement sustainable management plans, resource managers need to accurately forecast species abundance. Moreover, an ecosystem‐based approach to management requires forecasting the dynamics of all relevant species and the ability to anticipate indirect effects of management decisions. It is therefore crucial to determine which forecasting methods are most robust to observational and structural uncertainty. Here we describe a nonparametric method for multispecies forecasting and evaluate its performance relative to a suite of parametric models. We found that, in the presence of noise, it is often possible to obtain more accurate forecasts from the nonparametric method than from the model that was used to generate the data. The inclusion of data from additional species yielded a large improvement for the nonparametric model, a smaller improvement for the control model, and only a slight improvement for the alternative parametric models. These results suggest that flexible nonparametric modeling should be considered for ecosystem management.

Thermal reaction norms for growth vary among cohorts of Pacific cod (Gadus macrocephalus) - Thomas P. Hurst; Stephan B. Munch; Kate A. Lavelle (Marine Biology, 2012)

Flexible modeling for stock-recruitment relationships using Bayesian nonparametric mixtures - Kassandra Fronczyk; Athanasios Kottas; Stephan Munch (Environmental and Ecological Statistics, 2012)

Spatial scale and divergent patterns of variation in adapted traits in the ocean - Lyndie A. Hice; Tara A. Duffy; Stephan B. Munch; David O. Conover (Ecology Letters, 2012)
Ecology Letters (2012) Abstract The geography of adaptive genetic variation is crucial to species conservation yet poorly understood in marine systems. We analyse the spatial scale of genetic variation in traits that broadly display adaptation throughout the range of a highly dispersive marine species. We conducted common garden experiments on the Atlantic silverside, Menidia menidia , from 39 locations along its 3 000 km range thereby mapping genetic variation for growth rate, vertebral number and sex determination. Each trait displayed unique clinal patterns, with significant differences (adaptive or not) occurring over very small distances. Breakpoints in the cline differed among traits, corresponding only partially with presumed eco‐geographical boundaries. Because clinal patterns are unique to each selected character, neutral genes or those coding for a single character cannot serve as proxies for the genetic structure as a whole. Conservation plans designed to protect essential genetic subunits of a species will need to account for such complex spatial structures.

Thermal legacies: transgenerational effects of temperature on growth in a vertebrate - Santiago Salinas; Stephan B. Munch (Ecology Letters, 2012)
Ecology Letters (2011) Abstract Transgenerational plasticity (TGP), a generalisation of more widely studied maternal effects, occurs whenever environmental cues experienced by either parent prior to fertilisation results in a modification of offspring reaction norms. Such effects have been observed in many traits across many species. Despite enormous potential importance—particularly in an era of rapid climate change—TGP in thermal growth physiology has never been demonstrated for vertebrates. We provide the first evidence for thermal TGP in a vertebrate: given sufficient time, sheepshead minnows adaptively program their offspring for maximal growth at the present temperature. The change in growth over a single generation ( c . 30%) exceeds the single‐generation rate of adaptive evolution by an order of magnitude. If widespread, transgenerational effects on thermal performance may have important implications on physiology, ecology and contemporary evolution, and may significantly alter the extinction risk posed by changing climate.

High connectivity among locally adapted populations of a marine fish (Menidia menidia) - Lora M. Clarke; Stephan B. Munch; Simon R. Thorrold; David O. Conover (Ecology, 2010)
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.

The relationship between maternal phenotype and offspring quality: Do older mothers really produce the best offspring? - Dustin J. Marshall; Selina S. Heppell; Stephan B. Munch; Robert R. Warner (Ecology, 2010)
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.

Maladaptive changes in multiple traits caused by fishing: impediments to population recovery - Matthew R. Walsh; Stephan B. Munch; Susumu Chiba; David O. Conover (Ecology Letters, 2006)
Some overharvested fish populations fail to recover even after considerable reductions in fishing pressure. The reasons are unclear but may involve genetic changes in life history traits that are detrimental to population growth when natural environmental factors prevail. We empirically modelled this process by subjecting populations of a harvested marine fish, the Atlantic silverside, to experimental size‐biased fishing regimes over five generations and then measured correlated responses across multiple traits. Populations where large fish were selectively harvested (as in most fisheries) displayed substantial declines in fecundity, egg volume, larval size at hatch, larval viability, larval growth rates, food consumption rate and conversion efficiency, vertebral number, and willingness to forage. These genetically based changes in numerous traits generally reduce the capacity for population recovery.

A unified treatment of top‐down and bottom‐up control of reproduction in populations - Stephan B. Munch; Melissa L. Snover; George M. Watters; Marc Mangel (Ecology Letters, 2005)
Generalizations describing how top‐down and bottom‐up processes jointly influence the production of offspring (recruitment) and the number of reproducing adults are lacking. This is a deficiency because (1) it is widely recognized that both top‐down and bottom‐up processes are common in ecosystems; and (2) the relationship between the number of individuals recruiting and number of reproductively active individuals present in that population is of fundamental importance in all branches of ecology. Here we derive a model to consider the joint effects of top‐down and bottom‐up forcing in any ecosystem. In general, during the lifetime of a cohort, bottom‐up effects are likely to limit recruitment over longer periods of time than top‐down effects. Top‐down effects are likely to be most important early in the life history when potential recruits are small in size, and such effects will be more recognizable in small cohorts comprised of slowly growing individuals.