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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

Trade-offs between accuracy and interpretability in von Bertalanffy random-effects models of growth.

Better understanding of variation in growth will always be an important problem in ecology. Individual variation in growth can arise from a variety of processes; for example, individuals within a population vary in their intrinsic metabolic rates and behavioral traits, which may influence their foraging dynamics and access to resources. However, when adopting a growth model, we face trade-offs between model complexity, biological interpretability of parameters, and goodness of fit. We explore how different formulations of the von Bertalanffy growth function (vBGF) with individual random effects and environmental predictors affect these trade-offs. In the vBGF, the growth of an organism results from a dynamic balance between anabolic and catabolic processes. We start from a formulation of the vBGF that models the anabolic coefficient (q) as a function of the catabolic coefficient (k), a coefficient related to the properties of the environment (γ) and a parameter that determines the relative importance of behavior and environment in determining growth (ψ). We treat the vBGF parameters as a function of individual random effects and environmental variables. We use simulations to show how different functional forms and individual or group variability in the growth function's parameters provide a very flexible description of growth trajectories. We then consider a case study of two fish populations of Salmo marmoratus and Salmo trutta to test the goodness of fit and predictive power of the models, along with the biological interpretability of vBGF's parameters when using different model formulations. The best models, according to AIC, included individual variability in both k and γ and cohort as predictor of growth trajectories, and are consistent with the hypothesis that habitat selection is more important than behavioral and metabolic traits in determining lifetime growth trajectories of the two fish species. Model predictions of individual growth trajectories were largely more accurate than predictions based on mean size-at-age of fish. Our method shares information across individuals, and thus, for both fish populations investigated, allows using a single measurement early in the life of individual fish or cohort to obtain accurate predictions of lifetime individual or cohort size-at-age.

Within- and among-population variation in vital rates and population dynamics in a variable environment.

Understanding the causes of within- and among-population differences in vital rates, life histories, and population dynamics is a central topic in ecology. To understand how within- and among-population variation emerges, we need long-term studies that include episodic events and contrasting environmental conditions, data to characterize individual and shared variation, and statistical models that can tease apart shared and individual contribution to the observed variation. We used long-term tag-recapture data to investigate and estimate within- and among-population differences in vital rates, life histories, and population dynamics of marble trout Salmo marmoratus, an endemic freshwater salmonid with a narrow range. Only ten populations of pure marble trout persist in headwaters of Alpine rivers in western Slovenia. Marble trout populations are also threatened by floods and landslides, which have already caused the extinction of two populations in recent years. We estimated and determined causes of variation in growth, survival, and recruitment both within and among populations, and evaluated trade-offs between them. Specifically, we estimated the responses of these traits to variation in water temperature, density, sex, early life conditions, and extreme events. We found that the effects of population density on traits were mostly limited to the early stages of life and that growth trajectories were established early in life. We found no clear effects of water temperature on vital rates. Population density varied over time, with flash floods and debris flows causing massive mortalities (>55% decrease in survival with respect to years with no floods) and threatening population persistence. Apart from flood events, variation in population density within streams was largely determined by variation in recruitment, with survival of older fish being relatively constant over time within populations, but substantially different among populations. Marble trout show a fast to slow continuum of life histories, with slow growth associated with higher survival at the population level, possibly determined by food conditions and age at maturity. Our work provides unprecedented insight into the causes of variation in vital rates, life histories, and population dynamics in an endemic species that is teetering on the edge of extinction.

Avoiding tipping points in fisheries management through Gaussian process dynamic programming.

Model uncertainty and limited data are fundamental challenges to robust management of human intervention in a natural system. These challenges are acutely highlighted by concerns that many ecological systems may contain tipping points, such as Allee population sizes. Before a collapse, we do not know where the tipping points lie, if they exist at all. Hence, we know neither a complete model of the system dynamics nor do we have access to data in some large region of state space where such a tipping point might exist. We illustrate how a Bayesian non-parametric approach using a Gaussian process (GP) prior provides a flexible representation of this inherent uncertainty. We embed GPs in a stochastic dynamic programming framework in order to make robust management predictions with both model uncertainty and limited data. We use simulations to evaluate this approach as compared with the standard approach of using model selection to choose from a set of candidate models. We find that model selection erroneously favours models without tipping points, leading to harvest policies that guarantee extinction. The Gaussian process dynamic programming (GPDP) performs nearly as well as the true model and significantly outperforms standard approaches. We illustrate this using examples of simulated single-species dynamics, where the standard model selection approach should be most effective and find that it still fails to account for uncertainty appropriately and leads to population crashes, while management based on the GPDP does not, as it does not underestimate the uncertainty outside of the observed data.

Using grizzly bears to assess harvest-ecosystem tradeoffs in salmon fisheries.

Implementation of ecosystem-based fisheries management (EBFM) requires a clear conceptual and quantitative framework for assessing how different harvest options can modify benefits to ecosystem and human beneficiaries. We address this social-ecological need for Pacific salmon fisheries, which are economically valuable but intercept much of the annual pulse of nutrient subsidies that salmon provide to terrestrial and aquatic food webs. We used grizzly bears, vectors of salmon nutrients and animals with densities strongly coupled to salmon abundance, as surrogates for "salmon ecosystem" function. Combining salmon biomass and stock-recruitment data with stable isotope analysis, we assess potential tradeoffs between fishery yields and bear population densities for six sockeye salmon stocks in Bristol Bay, Alaska, and British Columbia (BC), Canada. For the coastal stocks, we find that both bear densities and fishery yields would increase substantially if ecosystem allocations of salmon increase from currently applied lower to upper goals and beyond. This aligning of benefits comes at a potential cost, however, with the possibility of forgoing harvests in low productivity years. In contrast, we detect acute tradeoffs between bear densities and fishery yields in interior stocks within the Fraser River, BC, where biomass from other salmon species is low. There, increasing salmon allocations to ecosystems would benefit threatened bear populations at the cost of reduced long-term yields. To resolve this conflict, we propose an EBFM goal that values fisheries and bears (and by extension, the ecosystem) equally. At such targets, ecosystem benefits are unexpectedly large compared with losses in fishery yields. To explore other management options, we generate tradeoff curves that provide stock-specific accounting of the expected loss to fishers and gain to bears as more salmon escape the fishery. Our approach, modified to suit multiple scenarios, provides a generalizable method to resolve conflicts over shared resources in other systems.

Stochastic dynamics of interacting haematopoietic stem cell niche lineages.

Since we still know very little about stem cells in their natural environment, it is useful to explore their dynamics through modelling and simulation, as well as experimentally. Most models of stem cell systems are based on deterministic differential equations that ignore the natural heterogeneity of stem cell populations. This is not appropriate at the level of individual cells and niches, when randomness is more likely to affect dynamics. In this paper, we introduce a fast stochastic method for simulating a metapopulation of stem cell niche lineages, that is, many sub-populations that together form a heterogeneous metapopulation, over time. By selecting the common limiting timestep, our method ensures that the entire metapopulation is simulated synchronously. This is important, as it allows us to introduce interactions between separate niche lineages, which would otherwise be impossible. We expand our method to enable the coupling of many lineages into niche groups, where differentiated cells are pooled within each niche group. Using this method, we explore the dynamics of the haematopoietic system from a demand control system perspective. We find that coupling together niche lineages allows the organism to regulate blood cell numbers as closely as possible to the homeostatic optimum. Furthermore, coupled lineages respond better than uncoupled ones to random perturbations, here the loss of some myeloid cells. This could imply that it is advantageous for an organism to connect together its niche lineages into groups. Our results suggest that a potential fruitful empirical direction will be to understand how stem cell descendants communicate with the niche and how cancer may arise as a result of a failure of such communication.

Determining individual variation in growth and its implication for life-history and population processes using the empirical Bayes method.

The differences in demographic and life-history processes between organisms living in the same population have important consequences for ecological and evolutionary dynamics. Modern statistical and computational methods allow the investigation of individual and shared (among homogeneous groups) determinants of the observed variation in growth. We use an Empirical Bayes approach to estimate individual and shared variation in somatic growth using a von Bertalanffy growth model with random effects. To illustrate the power and generality of the method, we consider two populations of marble trout Salmo marmoratus living in Slovenian streams, where individually tagged fish have been sampled for more than 15 years. We use year-of-birth cohort, population density during the first year of life, and individual random effects as potential predictors of the von Bertalanffy growth function's parameters k (rate of growth) and L∞ (asymptotic size). Our results showed that size ranks were largely maintained throughout marble trout lifetime in both populations. According to the Akaike Information Criterion (AIC), the best models showed different growth patterns for year-of-birth cohorts as well as the existence of substantial individual variation in growth trajectories after accounting for the cohort effect. For both populations, models including density during the first year of life showed that growth tended to decrease with increasing population density early in life. Model validation showed that predictions of individual growth trajectories using the random-effects model were more accurate than predictions based on mean size-at-age of fish.

Intercohort size structure dynamics of fire salamander larvae in ephemeral habitats: a mesocosm experiment.

The size structure of a larval population facilitates interaction asymmetries that, in turn, influence the dynamics of size-structure. In species that exhibit conspicuous aggressive interactions, the competitive effects of the smaller individuals may be overlooked. We manipulated initial size differences between two larval cohorts and young-cohort density of Salamandra infraimmaculata in mesocosms to determine: (1) whether young individuals function primarily as prey or as competitors of older and larger individuals; (2) the resulting dynamics of size variation; and (3) recruitment to the postmetamorph population. Intercohort size differences generally remained constant over time at low young-cohort densities, but reduced over time at high densities due to retardation of the old-cohort growth rate. This suggests a competitive advantage to the young cohort that outweighs the interference advantage of older cohorts previously documented in this species. The increase in mortality from desiccation due to high young-cohort density was an order of magnitude greater in the old cohort than in the young-cohort, further indicating size-dependent vulnerability to competition. However, the conditions least favorable to most of the old-cohort larvae (large size difference and high young-cohort density) promoted cannibalism. Among cannibals, mortality and time to metamorphosis decreased and sizes at metamorphosis increased substantially. Thus, a balance between the competitive advantage to young cohorts, and the interference and cannibalism advantage to old cohorts shapes larval size-structure dynamics. Larval densities and individual expression of cannibalism can shift this balance in opposite directions and alter relative recruitment rates from different cohorts.