Identifying causal networks is important for effective policy and management recommendations on climate, epidemiology, financial regulation, and much else. We introduce a method, based on nonlinear state space reconstruction, that can distinguish causality from correlation. It extends to nonseparable weakly connected dynamic systems (cases not covered by the current Granger causality paradigm). The approach is illustrated both by simple models (where, in contrast to the real world, we know the underlying equations/relations and so can check the validity of our method) and by application to real ecological systems, including the controversial sardine-anchovy-temperature problem.

Fishery management plans ignore the potential for evolutionary change in harvestable biomass. We subjected populations of an exploited fish (Menidia menidia) to large, small, or random size-selective harvest of adults over four generations. Harvested biomass evolved rapidly in directions counter to the size-dependent force of fishing mortality. Large-harvested populations initially produced the highest catch but quickly evolved a lower yield than controls. Small-harvested populations did the reverse. These shifts were caused by selection of genotypes with slower or faster rates of growth. Management tools that preserve natural genetic variation are necessary for long-term sustainable yield.It is well established that wild pest and pathogen populations may evolve in response to anthropogenic forces of mortality (1), but is the same true of fisheries? Fishing mortality is highly selective. Exploited stocks typically display greatly truncated size and age distributions that lack larger and/or older individuals (2-4). This occurs not only because fishers may seek to exploit large individuals but also because regulatory measures often impose minimum size or gear regulations that ensure selective harvest of larger fish. Such harvesting practices could favor genotypes with slower growth, earlier age at maturity, or other changes that would lower population productivity. Despite mounting evidence of rapid life history evolution in wild fish populations (5-8), the unexpectedly slow recovery of populations from overexploitation (9, 10), and warnings from theorists (3, 11), current models and management plans for sustainable yield ignore the Darwinian consequences of selective harvest.Failure to consider evolutionary processes in fisheries management continues in part because proof that size-selective mortality causes genetic changes in population productivity is lacking. Here, we present results from experimentally harvested captive populations of a marine fish that demonstrate evolutionary effects of size-selective mortality on somatic growth, yield, and population biomass.The Atlantic silverside, Menidia menidia, is a common marine fish along the North American east coast. Although landed commercially (mean annual landings in New York, from 1996 to 2000, were 20.5 metric tons), we chose this species as a model primarily for two other reasons. First, many of its life history characteristics are similar to those of other harvested marine species [e.g., high fecundity, small egg size (1 mm in diameter), external fertilization, spawning en masse, pelagic larvae, and schooling behavior], with one major exception. The short generation time of M. menidia (1 year) coupled with the ease with which large populations can be maintained in captivity enable experimental designs that would otherwise be impossible. Second, M. menidia from different latitudes display clinal adaptive genetic variation in somatic growth rate (12), a geographical pattern common to other harvested species (13-16). Hence, a key production trait (somatic grow...

Evidence shows that species interactions are not constant but change as the ecosystem shifts to new states. Although controlled experiments and model investigations demonstrate how nonlinear interactions can arise in principle, empirical tools to track and predict them in nature are lacking. Here we present a practical method, using available time-series data, to measure and forecast changing interactions in real systems, and identify the underlying mechanisms. The method is illustrated with model data from a marine mesocosm experiment and limnologic field data from Sparkling Lake, WI, USA. From simple to complex, these examples demonstrate the feasibility of quantifying, predicting and understanding state-dependent, nonlinear interactions as they occur in situ and in real time-a requirement for managing resources in a nonlinear, non-equilibrium world.

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.

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 Ecopath 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.

Knowledge of geographic and temporal scales of adaptive genetic variation is crucial to species conservation, yet understanding of these phenomena, particularly in marine systems, is scant. Until recently, the belief has been that because most marine species have highly dispersive or mobile life stages, local adaptation could occur only on broad geographic scales. This view is supported by comparatively low levels of genetic variation among populations as detected by neutral markers. Similarly, the time scale of adaptive divergence has also been assumed to be very long, requiring thousands of generations. Recent studies of a variety of species have challenged these beliefs. First, there is strong evidence of geographically structured local adaptation in physiological and morphological traits. Second, the proportion of quantitative trait variation at the among‐population level (QST) is much higher than it is for neutral markers (FST) and these two metrics of genetic variation are poorly correlated. Third, evidence that selection is a potent evolutionary force capable of sustaining adaptive divergence on contemporary time scales is summarized. The differing spatial and temporal scales of adaptive v. neutral genetic divergence call for a new paradigm in thinking about the relationship between phenogeography (the geography of phenotypic variation) and phylogeography (the geography of lineages) in marine species. The idea that contemporary selective processes can cause fine‐scale spatial and temporal divergence underscores the need for a new emphasis on Darwinian fishery science.

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.

Compensatory or catch-up growth (CG) is widely observed following periods of resource deprivation. Because of this commonness, it is generally assumed that compensatory growth is adaptive, but most theory to date has explicitly ignored considerations of fitness. Following a period of deprivation, when resources become plentiful again, individuals may not respond at all and continue on a "normal" trajectory from a smaller size at age, may exhibit faster-than-normal growth immediately following the end of the period, or may adopt a growth strategy that involves faster-than-normal growth at some later time. Compensating individuals may also overtake control individuals who have been growing normally throughout. We hypothesize that the key to understanding CG is that growth leads to the accumulation of damage at the cellular level that is expressed (and thus must be modeled) at the level of the organism. We show that a life-history model incorporating the mortality consequences of both size and damage provides a framework for understanding compensatory growth. We use the theory to classify physiological and life-history characteristics for which CG is predicted to be the optimal response to deprivation.