A benefit-risk analysis for biological control introductions based on the protection of native biodiversity.

The release of biological control agents has been an important means of controlling invasive species for over 150 years. While these releases have led to the sustainable control of over 250 invasive pest and weed species worldwide, a minority have caused environmental harm. A growing recognition of the risks of biological control led to a focus on risk assessment beginning in the 1990s along with a precipitous decline in releases. While this new focus greatly improved the safety of biological control, it came at the cost of lost opportunities to solve environmental problems associated with invasive species. A framework that incorporates benefits and risks of biological control is thus needed to understand the net environmental effects of biological control releases. We introduce such a framework, using native biodiversity as the common currency for both benefits and risks. The model is based on interactions among four categories of organisms: (1) the biological control agent, (2) the invasive species (pest or weed) targeted by the agent, (3) one or more native species that stand to benefit from the control of the target species, and (4) one or more native species that are at risk of being harmed by the released biological control agent. Conservation values of the potentially benefited and harmed native species are incorporated as well, and they are weighted according to three axes: vulnerability to extinction, the ecosystem services provided, and cultural significance. Further, we incorporate the potential for indirect risks to native species, which we consider will result mainly from the ecological process of agent enrichment that may occur if the agent exploits but does not control the target pest or weed. We illustrate the use of this framework by retrospectively analyzing the release of the vedalia beetle, Novius (= Rodolia) cardinalis, to control the cottony cushion scale, Icerya purchasi, in the Galapagos Islands. While the framework is particularly adaptable to biological control releases in natural areas, it can also be used in managed settings, where biological control protects native species through the reduction of pesticide use.

Size-dependence of food intake and mortality interact with temperature and seasonality to drive diversity in fish life histories.

Understanding how growth and reproduction will adapt to changing environmental conditions is a fundamental question in evolutionary ecology, but predicting the responses of specific taxa is challenging. Analyses of the physiological effects of climate change upon life history evolution rarely consider alternative hypothesized mechanisms, such as size-dependent foraging and the risk of predation, simultaneously shaping optimal growth patterns. To test for interactions between these mechanisms, we embedded a state-dependent energetic model in an ecosystem size-spectrum to ask whether prey availability (foraging) and risk of predation experienced by individual fish can explain observed diversity in life histories of fishes. We found that asymptotic growth emerged from size-based foraging and reproductive and mortality patterns in the context of ecosystem food web interactions. While more productive ecosystems led to larger body sizes, the effects of temperature on metabolic costs had only small effects on size. To validate our model, we ran it for abiotic scenarios corresponding to the ecological lifestyles of three tuna species, considering environments that included seasonal variation in temperature. We successfully predicted realistic patterns of growth, reproduction, and mortality of all three tuna species. We found that individuals grew larger when environmental conditions varied seasonally, and spawning was restricted to part of the year (corresponding to their migration from temperate to tropical waters). Growing larger was advantageous because foraging and spawning opportunities were seasonally constrained. This mechanism could explain the evolution of gigantism in temperate tunas. Our approach addresses variation in food availability and individual risk as well as metabolic processes and offers a promising approach to understand fish life-history responses to changing ocean conditions.

Effects of time spent in pregnancy or brooding on immunocompetence.

Sexes of a species may show different characteristics beyond the differences in their sexual organs and such sexual dimorphism often occurs in the level of immune response when exposed to pathogens (immunocompetence). In general, females have increased longevity relative to males, which is associated with higher immunocompetence. However, males have higher immunocompetence in some species, such as pipefishes and seahorses. Experimental evidence suggests that this could be because males, rather than females, carry fertilized eggs to birth in these species. This observation suggests that an increase in immunocompetence may be related to the level of parental investment and not to a particular sex. We use state-dependent life-history theory to study optimal investment in offspring production relative to parent immunocompetence, varying the relative time that a parent spends in brooding or pregnancy within a breeding cycle. When offspring is dependent on a parent's survival for a large part of the breeding cycle, we predict higher investments in immunity and longer life expectancies.

Operational analysis for COVID-19 testing: Determining the risk from asymptomatic infections.

Testing remains a key tool for managing health care and making health policy during the coronavirus pandemic, and it will probably be important in future pandemics. Because of false negative and false positive tests, the observed fraction of positive tests-the surface positivity-is generally different from the fraction of infected individuals (the incidence rate of the disease). In this paper a previous method for translating surface positivity to a point estimate for incidence rate, then to an appropriate range of values for the incidence rate consistent with the model and data (the test range), and finally to the risk (the probability of including one infected individual) associated with groups of different sizes is illustrated. The method is then extended to include asymptomatic infections. To do so, the process of testing is modeled using both analysis and Monte Carlo simulation. Doing so shows that it is possible to determine point estimates for the fraction of infected and symptomatic individuals, the fraction of uninfected and symptomatic individuals, and the ratio of infected asymptomatic individuals to infected symptomatic individuals. Inclusion of symptom status generalizes the test range from an interval to a region in the plane determined by the incidence rate and the ratio of asymptomatic to symptomatic infections; likelihood methods can be used to determine the contour of the rest region. Points on this contour can be used to compute the risk (defined as the probability of including one asymptomatic infected individual) in groups of different sizes. These results have operational implications that include: positivity rate is not incidence rate; symptom status at testing can provide valuable information about asymptomatic infections; collecting information on time since putative virus exposure at testing is valuable for determining point estimates and test ranges; risk is a graded (rather than binary) function of group size; and because the information provided by testing becomes more accurate with more tests but at a decreasing rate, it is possible to over-test fixed spatial regions. The paper concludes with limitations of the method and directions for future work.

The influence of prey availability on behavioral decisions and reproductive success of a central-place forager during lactation.

Marine central-place foragers are increasingly faced with altered prey landscapes, necessitating predictions of the impact of such changes on behavior, reproductive success, and population dynamics. We used state-dependent behavioral life history theory implemented via Stochastic Dynamic Programming (SDP) to explore the influence of changes in prey distribution and energy gain from foraging on the behavior and reproductive success of a central place forager during lactation. Our work is motivated by northern fur seals (Callorhinus ursinus) because of the ongoing population decline of the Eastern Pacific stock and projected declines in biomass of walleye pollock (Gadus chalcogrammus), a key fur seal prey species in the eastern Bering Sea. We also explored how changes in female and pup metabolic rates, body size, and lactation duration affected model output to provide insight into traits that might experience selective pressure in response to reductions in prey availability. Simulated females adopted a central-place foraging strategy after an initial extended period spent on land (4.7-8.3 days). Trip durations increased as the high energy prey patch moved farther from land or when the energy gain from foraging decreased. Increases in trip duration adversely affected pup growth rates and wean mass despite attempts to compensate by increasing land durations. Metabolic rate changes had the largest impacts on pup wean mass, with reductions in a pup's metabolic rate allowing females to successfully forage at distances of 600+ km from land for up to 15+ days. Our results indicate that without physiological adaptations, a rookery is unlikely to be viable if the primary foraging grounds are 400 km or farther from the rookery. To achieve pup growth rates characteristic of a population experiencing rapid growth, model results indicate the primary foraging grounds need to be <150 km from the rookery.

Population processes in cyber system variability.

Variability is inherent to cyber systems. Here, we introduce ideas from stochastic population biology to describe the properties of two broad kinds of cyber systems. First, we assume that each of N0 components can be in only one of two states: functional or nonfunctional. We model this situation as a Markov process that describes the transitions between functional and nonfunctional states. We derive an equation for the probability that an individual cyber component is functional and use stochastic simulation to develop intuition about the dynamics of individual cyber components. We introduce a metric of performance of the system of N0 components that depends on the numbers of functional and nonfunctional components. We numerically solve the forward Kolmogorov (or Fokker-Planck) equation for the number of functional components at time t, given the initial number of functional components. We derive a Gaussian approximation for the solution of the forward equation so that the properties of the system with many components can be determined from the transition probabilities of an individual component, allowing scaling to very large systems. Second, we consider the situation in which the operating system (OS) of cyber components is updated in time. We motivate the question of OS in use as a function of the most recent OS release with data from a network of desktop computers. We begin the analysis by specifying a temporal schedule of OS updates and the probability of transitioning from the current OS to a more recent one. We use a stochastic simulation to capture the pattern of the motivating data, and derive the forward equation for the OS of an individual computer at any time. We then include compromise of OSs to compute that a cyber component has an unexploited OS at any time. We conclude that an interdisciplinary approach to the variability of cyber systems can shed new light on the properties of those systems and offers new and exciting ways to understand them.

Gray whale habitat use and reproductive success during seismic surveys near their feeding grounds: comparing state-dependent life history models and field data.

We used a stochastic dynamic programming (SDP) model to quantify the consequences of disturbance on pregnant western gray whales during one foraging season. The SDP model has a firm basis in bioenergetics, but detailed knowledge of minimum reproductive length of females (Lmin) and the relationship between length and reproductive success (Rfit) was lacking. We varied model assumptions to determine their effects on predictions of habitat use, proportion of animals disturbed, reproductive success, and the effects of disturbance. Smaller Lmin values led to higher predicted nearshore habitat use. Changes in Lmin and Rfit had little effect on predictions of the effect of disturbance. Reproductive success increased with increased Lmin and with higher probability of reproductive success by length. Multiple seismic surveys were conducted in 2015 off the northeast coast of Sakhalin Island, with concomitant benthic prey surveys, photo-identification studies, and whale distribution sampling, thus providing a unique opportunity to compare output from SDP models with empirical observations. SDP model predictions of reproductive success and habitat use were similar with and without acoustic disturbance, and SDP predictions of reproductive success and large-scale habitat use were generally similar to values and trends in the data. However, empirical estimates of the proportion of pregnant females nearshore were much higher than SDP model predictions (a large effect, measured by Cohen's d) during the first week, and the SDP model overestimated whale density in the south and underestimated density around the mouth of Piltun Bay. Such differences in nearshore habitat use would not affect SDP predictions of reproductive success or survival under the current seismic air gun disturbance scenario.

Predicting the population consequences of acoustic disturbance, with application to an endangered gray whale population.

Acoustic disturbance is a growing conservation concern for wildlife populations because it can elicit physiological and behavioral responses that can have cascading impacts on population dynamics. State-dependent behavioral and life history models implemented via Stochastic Dynamic Programming (SDP) provide a natural framework for quantifying biologically meaningful population changes resulting from disturbance by linking environment, physiology, and metrics of fitness. We developed an SDP model using the endangered western gray whale (Eschrichtius robustus) as a case study because they experience acoustic disturbance on their summer foraging grounds. We modeled the behavior and physiological dynamics of pregnant females as they arrived on the feeding grounds and predicted the probability of female and offspring survival, with and without acoustic disturbance and in the presence/absence of high prey availability. Upon arrival in mid-May, pregnant females initially exhibited relatively random behavior before they transitioned to intensive feeding that resulted in continual fat mass gain until departure. This shift in behavior co-occurred with a change in spatial distribution; early in the season, whales were more equally distributed among foraging areas with moderate to high energy availability, whereas by mid-July whales transitioned to predominate use of the location that had the highest energy availability. Exclusion from energy-rich offshore areas led to reproductive failure and in extreme cases, mortality of adult females that had lasting impacts on population dynamics. Simulated disturbances in nearshore foraging areas had little to no impact on female survival or reproductive success at the population level. At the individual level, the impact of disturbance was unequally distributed across females of different lengths, both with respect to the number of times an individual was disturbed and the impact of disturbance on vital rates. Our results highlight the susceptibility of large capital breeders to reductions in prey availability, and indicate that who, where, and when individuals are disturbed are likely to be important considerations when assessing the impacts of acoustic activities. This model provides a framework to inform planned acoustic disturbances and assess the effectiveness of mitigation strategies for large capital breeders.

Reproductive hyperallometry and managing the world's fisheries.

Marine fisheries are an essential component of global food security, but many are close to their limits and some are overfished. The models that guide the management of these fisheries almost always assume reproduction is proportional to mass (isometry), when fecundity generally increases disproportionately to mass (hyperallometry). Judged against several management reference points, we show that assuming isometry overestimates the replenishment potential of exploited fish stocks by 22% (range: 2% to 78%) for 32 of the world's largest fisheries, risking systematic overharvesting. We calculate that target catches based on assumptions of isometry are more than double those based on assumptions of hyperallometry for most species, such that common reference points are set twice as high as they should be to maintain the target level of replenishment. We also show that hyperallometric reproduction provides opportunities for increasing the efficacy of tools that are underused in standard fisheries management, such as protected areas or harvest slot limits. Adopting management strategies that conserve large, hyperfecund fish may, in some instances, result in higher yields relative to traditional approaches. We recommend that future assessment of reference points and quotas include reproductive hyperallometry unless there is clear evidence that it does not occur in that species.

A latitudinal gradient in thermal transgenerational plasticity and a test of theory.

Transgenerational plasticity (TGP) occurs when phenotypes are shaped by the environment in both the current and preceding generations. Transgenerational responses to rainfall, CO2 and temperature suggest that TGP may play an important role in how species cope with climate change. However, little is known about how TGP will evolve as climate change continues. Here, we provide a quantitative test of the hypothesis that the predictability of the environment influences the magnitude of the transgenerational response. To do so, we take advantage of the latitudinal decrease in the predictability of temperatures in near shore waters along the US East Coast. Using sheepshead minnows (Cyprinodon variegatus) from South Carolina, Maryland, and Connecticut, we found the first evidence for a latitudinal gradient in thermal TGP. Moreover, the degree of TGP in these populations depends linearly on the decorrelation time for temperature, providing support for the hypothesis that thermal predictability drives the evolution of these traits.

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.

Propensity for Risk in Reproductive Strategy Affects Susceptibility to Anthropogenic Disturbance.

AbstractAnimals initiate, interrupt, or invest resources in reproduction in light of their physiology and the environment. The energetic risks entailed in an individual's reproductive strategy can influence the ability to cope with additional stressors, such as anthropogenic climate change and disturbance. To explore the trade-offs between internal state, external resource availability, and reproduction, we applied state-dependent life-history theory (SDLHT) to a dynamic energy budget (DEB) model for long-finned pilot whales (Globicephala melas). We investigated the reproductive strategies emerging from the interplay between fitness maximization and propensity to take energetic risks, as well as the resulting susceptibility of individual vital rates to disturbance. Without disturbance, facultative reproductive behavior from SDLHT and fixed rules in the DEB model led to comparable individual fitness. However, under disturbance, the reproductive strategies emerging from SDLHT increased vulnerability to energetic risks, resulting in lower fitness than fixed rules. These fragile strategies might therefore be unlikely to evolve in the first place. Heterogeneous resource availability favored more cautious (and thus more robust) strategies, particularly when knowledge of resource variation was accurate. Our results demonstrate that the assumptions regarding the dynamic trade-offs underlying an individual's decision-making can have important consequences for predicting the effects of anthropogenic stressors on wildlife populations.

Global reconstruction of life-history strategies: A case study using tunas.

Measuring the demographic parameters of exploited populations is central to predicting their vulnerability and extinction risk. However, current rates of population decline and species loss greatly outpace our ability to empirically monitor all populations that are potentially threatened.The scale of this problem cannot be addressed through additional data collection alone, and therefore it is a common practice to conduct population assessments based on surrogate data collected from similar species. However, this approach introduces biases and imprecisions that are difficult to quantify. Recent developments in hierarchical modelling have enabled missing values to be reconstructed based on the correlations between available life-history data, linking similar species based on phylogeny and environmental conditions.However, these methods cannot resolve life-history variability among populations or species that are closely placed spatially or taxonomically. Here, theoretically motivated constraints that align with life-history theory offer a new avenue for addressing this problem. We describe a Bayesian hierarchical approach that combines fragmented, multispecies and multi-population data with established life-history theory, in order to objectively determine similarity between populations based on trait correlations (life-history trade-offs) obtained from model fitting.We reconstruct 59 unobserved life-history parameters for 23 populations of tuna that sustain some of the world's most valuable fisheries. Testing by cross-validation across different scenarios indicated that life-histories were accurately reconstructed when information was available for other populations of the same species. The reconstruction of several traits was also accurate for species represented by a single population, although credible intervals increased dramatically. Synthesis and applications. The described Bayesian hierarchical method provides access to life-history traits that are difficult to measure directly and reconstructs missing life-history information useful for assessing populations and species that are directly or indirectly affected by human exploitation of natural resources. The method is particularly useful for examining populations that are spatially or taxonomically similar, and the reconstructed life-history strategies described for the principal market tunas have immediate application to the world-wide management of these fisheries.

Modeling optimal responses and fitness consequences in a changing Arctic.

Animals must balance a series of costs and benefits while trying to maximize their fitness. For example, an individual may need to choose how much energy to allocate to reproduction versus growth, or how much time to spend on vigilance versus foraging. Their decisions depend on complex interactions between environmental conditions, behavioral plasticity, reproductive biology, and energetic demands. As animals respond to novel environmental conditions caused by climate change, the optimal decisions may shift. Stochastic dynamic programming provides a flexible modeling framework with which to explore these trade-offs, but this method has not yet been used to study possible changes in optimal trade-offs caused by climate change. We created a stochastic dynamic programming model capturing trade-off decisions required by an individual adult female polar bear (Ursus maritimus) as well as the fitness consequences of her decisions. We predicted optimal foraging decisions throughout her lifetime as well as the energetic thresholds below which it is optimal for her to abandon a reproductive attempt. To explore the effects of climate change, we shortened the spring feeding period by up to 3 weeks, which led to predictions of riskier foraging behavior and higher reproductive thresholds. The resulting changes in fitness may be interpreted as a best-case scenario, where bears adapt instantaneously and optimally to new environmental conditions. If the spring feeding period was reduced by 1 week, her expected fitness declined by 15%, and if reduced by 3 weeks, expected fitness declined by 68%. This demonstrates an effective way to explore a species' optimal response to a changing landscape of costs and benefits and highlights the fact that small annual effects can result in large cumulative changes in expected lifetime fitness.

Overcoming the Data Crisis in Biodiversity Conservation.

How can we track population trends when monitoring data are sparse? Population declines can go undetected, despite ongoing threats. For example, only one of every 200 harvested species are monitored. This gap leads to uncertainty about the seriousness of declines and hampers effective conservation. Collecting more data is important, but we can also make better use of existing information. Prior knowledge of physiology, life history, and community ecology can be used to inform population models. Additionally, in multispecies models, information can be shared among taxa based on phylogenetic, spatial, or temporal proximity. By exploiting generalities across species that share evolutionary or ecological characteristics within Bayesian hierarchical models, we can fill crucial gaps in the assessment of species' status with unparalleled quantitative rigor.

A Dynamic State Model of Migratory Behavior and Physiology to Assess the Consequences of Environmental Variation and Anthropogenic Disturbance on Marine Vertebrates.

Integrating behavior and physiology is critical to formulating new hypotheses on the evolution of animal life-history strategies. Migratory capital breeders acquire most of the energy they need to sustain migration, gestation, and lactation before parturition. Therefore, when predicting the impact of environmental variation on such species, a mechanistic understanding of the physiology of their migratory behavior is required. Using baleen whales as a model system, we developed a dynamic state variable model that captures the interplay among behavioral decisions, energy, reproductive needs, and the environment. We applied the framework to blue whales (Balaenoptera musculus) in the eastern North Pacific Ocean and explored the effects of environmental and anthropogenic perturbations on female reproductive success. We demonstrate the emergence of migration to track prey resources, enabling us to quantify the trade-offs among capital breeding, body condition, and metabolic expenses. We predict that periodic climatic oscillations affect reproductive success less than unprecedented environmental changes do. The effect of localized, acute anthropogenic impacts depended on whales' behavioral response to the disturbance; chronic, but weaker, disturbances had little effect on reproductive success. Because we link behavior and vital rates by modeling individuals' energetic budgets, we provide a general framework to investigate the ecology of migration and assess the population consequences of disturbance, while identifying critical knowledge gaps.

Size-conditional smolting and the response of Carmel River steelhead to two decades of conservation efforts.

Threshold effects are common in ecosystems and can generate counterintuitive outcomes in management interventions. A threshold effect proposed for steelhead trout (Oncorhynchus mykiss) is size-conditional smolting and marine survival. Steelhead are anadromous, maturing in the ocean but migrating to freshwater to spawn, where their offspring reside for one or more years before smolting-physiologically transforming to a saltwater form-and migrating to the ocean. In conditional smolting, juveniles transform only if growth exceeds a threshold body size prior to migration season, and subsequent marine survival correlates with size at ocean entry. Conditional smolting suggests that efforts to improve freshwater survival of juveniles may reduce smolt success if they increase competition and reduce growth. Using model-selection techniques, we asked if this effect explained declining numbers of adult Carmel River steelhead. This threatened population has been the focus of two decades of habitat restoration, as well as active translocation and captive-rearing of juveniles stranded in seasonally dewatered channels. In the top-ranked model selected by information-theoretic criteria, adult decline was linked to reduced juvenile growth rates in the lower river, consistent with the conditional smolting hypothesis. According to model inference, since 2005 most returning adult steelhead were captively-reared. However, a lower-ranked model without conditional smolting also had modest support, and suggested a negative effect of captive rearing. Translocations of juvenile fish to perennial reaches may have reduced the steelhead run slightly by raising competition, but this effect is confounded in the data with effects of river flow on growth. Efforts to recover Carmel River steelhead will probably be more successful if they focus on conditions promoting rapid growth in the river. Our analysis clearly favored a role for size-conditional smolting and marine survival in the decline of the population, but did not definitively rule out alternative explanations.

Genetic and life-history consequences of extreme climate events.

Climate change is predicted to increase the frequency and intensity of extreme climate events. Tests on empirical data of theory-based predictions on the consequences of extreme climate events are thus necessary to understand the adaptive potential of species and the overarching risks associated with all aspects of climate change. We tested predictions on the genetic and life-history consequences of extreme climate events in two populations of marble trout Salmo marmoratus that have experienced severe demographic bottlenecks due to flash floods. We combined long-term field and genotyping data with pedigree reconstruction in a theory-based framework. Our results show that after flash floods, reproduction occurred at a younger age in one population. In both populations, we found the highest reproductive variance in the first cohort born after the floods due to a combination of fewer parents and higher early survival of offspring. A small number of parents allowed for demographic recovery after the floods, but the genetic bottleneck further reduced genetic diversity in both populations. Our results also elucidate some of the mechanisms responsible for a greater prevalence of faster life histories after the extreme event.

Whales, science, and scientific whaling in the International Court of Justice.

I provide a brief review of the origins of the International Convention on the Regulation of Whaling and the failure to successfully regulate whaling that led to the commercial moratorium in 1986. I then describe the Japanese Whale Research Programs Under Special Permit in the Antarctica (JARPA I, JARPA II) and the origins of the case Whaling in the Antarctic (Australia v. Japan: New Zealand Intervening) in the International Court of Justice. I explain that the International Court of Justice chose to conduct an objective review of JARPA II, the standard that it used for the review, and the pathway that it took to adjudicate the case without providing a definition of science to be used in international law. I conclude with a brief discussion of the implications of the Judgment for the International Convention on the Regulation of Whaling, and the International Whaling Commission in particular, for other international treaties, and for the interaction of science and law more generally.