Stochastic population dynamics in populations of western terrestrial garter snakes with divergent life histories

Comparative evaluations of population dynamics in species with temporal and spatial variation in life-history traits are rare because they require long-term demographic time series from multiple populations. We present such an analysis using demographic data collected during the interval 1978-1996 for six populations of western terrestrial garter snakes (Thamnophis elegans) from two evolutionarily divergent ecotypes. Three replicate populations from a slow-living ecotype, found in mountain meadows of northeastern California, were characterized by individuals that develop slowly, mature late, reproduce infrequently with small reproductive effort, and live longer than individuals of three populations of a fast-living ecotype found at lakeshore locales. We constructed matrix population models for each of the populations based on 8-13 years of data per population and analyzed both deterministic dynamics based on mean annual vital rates and stochastic dynamics incorporating annual variation in vital rates. (1) Contributions of highly variable vital rates to fitness (lambda(s)) were buffered against the negative effects of stochastic variation, and this relationship was consistent with differences between the meadow (M-slow) and lakeshore (L-fast) ecotypes. (2) Annual variation in the proportion of gravid females had the greatest negative effect among all vital rates on lambda(s). The magnitude of variation in the proportion of gravid females and its effect on lambda(s) was greater in M-slow than L-fast populations. (3) Variation in the proportion of gravid females, in turn, depended on annual variation in prey availability, and its effect on lambda(s) was 4 23 times greater in M-slow than L-fast populations. In addition to differences in stochastic dynamics between ecotypes, we also found higher mean mortality rates across all age classes in the L-fast populations. Our results suggest that both deterministic and stochastic selective forces have affected the evolution of divergent life-history traits in the two ecotypes, which, in turn, affect population dynamics. M-slow populations have evolved life-history traits that buffer fitness against direct effects of variation in reproduction and that spread lifetime reproduction across a greater number of reproductive bouts. These results highlight the importance of long-term demographic and environmental monitoring and of incorporating temporal dynamics into empirical studies of life-history evolution.     

Stochastic growth reduces population fluctuations in Daphnia-algal systems

Deterministic, size-structured models are widely used to describe consumer-resource interactions. Such models typically ignore potentially large random variability in juvenile development rates. We present simple representations of this variability and show five approaches to calculating the model parameters for Daphnia pulex interacting with its algal food. Using our parameterized models of growth variability, we investigate the robustness of a recently proposed stabilizing mechanism for Daphnia populations. Growth rate variability increases the range of enrichments over which small-amplitude cycles or quasi-cycles occur, thus increasing the plausibility that the underlying mechanism contributes to the prevalence of small-amplitude cycles in the field and in experiments. More generally, our approach allows us to relate commonly available information on variance of development times to population stability.     

Alaska’s Freshwater Resources: Issues Affecting Local and International Interests1

Alessa, Lilian, Mark Altaweel, Andrew Kliskey, Christopher Bone, William Schnabel, and Kalb Stevenson, 2011. Alaska’s Freshwater Resources: Issues Affecting Local and International Interests. Journal of the American Water Resources Association (JAWRA) 47(1):143‐157. DOI: 10.1111/j.1752‐1688.2010.00498.x Abstract: The State of Alaska faces a broad range of freshwater challenges including limited resource access in rural communities, increasing freshwater use, and a pressing need to better understand and prepare for climate‐driven change. Despite these significant issues, Alaska is relatively water‐rich and far more equipped to address its water resource concerns compared with other regions of the world. Globally, simultaneous and rapid water stresses have influenced and complicated conflicts and are motivating nations to develop markets and trade as one of the primary means to manage their needs for this resource. This paper presents these interacting issues in the context of Alaska’s relationship with a world undergoing significant social and ecological changes that affect freshwater supplies. We present the challenges faced by Alaska in the context of a larger global perspective, and briefly explore the relative effects these issues have on local, regional, and global scales. We present the argument that Alaska needs to develop more robust institutions and policies that can alleviate both household concerns and ensure that Alaska plays a significant role in the international freshwater arena for its long‐term resilience.     

Rebuilding and strengthening health systems and providing basic health services in fragile states

The international community has compelling humanitarian, political, security and economic reasons to engage in rebuilding and strengthening health systems in fragile states. Improvements in health services and systems help to strengthen civil society and to restore legitimacy to governments. Effective engagement with fragile states to inform the design of health programmes and selection of interventions depends on donor coordination and an understanding of health system challenges. Planning requires consideration of allocation (services to be delivered), production (organisation of services), distribution (beneficiaries of services) and financing. The criteria for selecting interventions are: their impact on major health problems; effectiveness; the possibility of scale-up; equity; and sustainability. There are various options for financing and models of engagement, but support should always combine short-term relief with longer-term development. Stakeholders should aim not only to save lives and protect health but also to bolster nations' ability to deliver good-quality services in the long run.     

Predicting local population distributions around a central shelter based on a predation risk-growth trade-off

Animals face trade-offs between predation risk and foraging success depending on their location in the landscape; for example, individuals that remain near a common shelter may be safe from predation but incur stronger competition for resources. Despite a long tradition of theoretical exploration of the relationships among foraging success, conspecific competition, predation risk, and population distribution in a heterogeneous environment, the scenario we describe here has not been explored theoretically. We construct a model of habitat use rules to predict the distribution of a local population (prey sharing a common shelter and foraging across surrounding habitats). Our model describes realized habitat quality as a ratio of density- and location-dependent mortality to density-dependent growth. We explore how the prey distribution around a shelter is expected to change as the parameters governing the strength of density dependence, landscape characteristics, and local abundance vary. Within the range of parameters where prey spend some time away from shelter but remain site-attached, the prey density decreases away from shelter. As the distance at which prey react to predators increases, the population range generally increases. At intermediate reaction distances, however, increases in the reaction distance lead to decreases in the maximum foraging distance because of increased evenness in the population distribution. As total abundance increases, the population range increases, average population density increases, and realized quality decreases. The magnitude of these changes differs in, for example, ‘high-’ and ‘low-visibility’ landscapes where prey can detect predators at different distances.     

Body size and sexual selection in the koala

Sexual selection is often characterized by polygynous breeding systems, size dimorphism, and skewed operational sex ratios. Koalas are sexually dimorphic in multiple domains, yet are absent from the literature on sexual selection and the structure of their mating system is unclear. We provide the first documentation of the strength of sexual selection in koalas by using microsatellite markers to identify sires. We combine the genetic data with morphological data in order to assess the role of body size in regulating reproductive output. During our 4-year study, 37% of males were identified as possible sires. Males were significantly larger than females, with sires heavier than non-sires. Male body mass correlated with annual reproductive output, with Crow’s Index of Opportunity for Selection revealing that variation in male reproductive success was threefold higher than that of females. Since it appears that male koalas rarely engage in physical confrontations over access to females, size dimorphism could be based upon non-agonistic competition and/or female mate choice. We propose that size dimorphism in koalas evolved as a consequence of endurance rivalry promoting vocal sexual advertisements that attract females. We suggest that female choice is a key mediator of male reproductive output.     

Bayesian networks make LOPA more effective,QRA more transparent and flexible,and thus safety more definable!

Quantitative risk analysis is in principle an ideal method to map one’s risks, but it has limitations due to the complexity of models, scarcity of data, remaining uncertainties, and above all because effort, cost, and time requirements are heavy. Also, software is not cheap, the calculations are not quite transparent, and the flexibility to look at various scenarios and at preventive and protective options is limited. So, the method is considered as a last resort for determination of risks. Simpler methods such as LOPA that focus on a particular scenario and assessment of protection for a defined initiating event are more popular. LOPA may however not cover the whole range of credible scenarios, and calamitous surprises may emerge.In the past few decades, Artificial Intelligence university groups, such as the Decision Systems Laboratory of the University of Pittsburgh, have developed Bayesian approaches to support decision making in situations where one has to weigh gains and costs versus risks. This paper will describe details of such an approach and will provide some examples of both discrete random variables, such as the probability values in a LOPA, and continuous distributions, which can better reflect the uncertainty in data.     

Should I stay or should I go? An experimental study of health and economic government policies following a severe biological agent release

Extensive research has explored policy challenges associated with preparing and responding to a large-scale biological release. A key component in recovery strategy development that has received less attention is the understanding of government policy influence on the impacted populations’ migratory decisions. This study experimentally manipulates health and economic government policies during response and recovery to assess the extent to which public migration is contingent on the level of government intervention. Set immediately following a large-scale anthrax release in San Francisco, we use a five episode video scenario to describe details about the environmental impacts of the disaster, emergency response procedures, and clean-up operations. Within these video segments, the extent of government involvement in economic and health risk policies is manipulated. Using these manipulations as predictors, we track how varying levels of government risk signals influence migration behavior at three distinct decision points during disaster recovery. In addition, two belief scales and two scales of emotion (affect) are included as predictors to explore the potential for their mediating role in explaining intentions to migrate. We find that the decision to migrate is highly context-sensitive, with each decision point showing a unique combination of significant predictors influencing decision making. At 19 days following the anthrax release, the health risk policy manipulation has both a direct and indirect effect on migration behavior. At 3 months, the influence of the health risk policy manipulation is mediated by beliefs, and at 1 year, only indirect effects associated with affect and beliefs influence migration.     

Socioeconomic evaluation of the impact of natural resource stressors on human-use services in the Great Lakes environment: A Lake Michigan case study

The Great Lakes watershed is home to over 40 million people (Canadian and U.S.) who depend on a healthy Great Lakes ecosystem for economic, societal, and personal vitality. The challenge to policymakers and the public is to balance economic benefits with the need to conserve and replenish regional natural resources in a manner that ensures long term prosperity. Nine critical broad-spectrum stressors of ecological services are identified, which include pollution and contamination, agricultural erosion, non-native species, degraded recreational resources, loss of wetlands habitat, climate change, risk of clean water shortage, vanishing sand dunes, and population overcrowding. Many of these stressors overlap. For example, mining activities alone can create stress in at least five of these categories. The focus groups were conducted to examine the public’s awareness of, concern with, and willingness to expend resources on these stressors. This helped generate a grouping of stressors that the public is especially concerned about, those they care little about, and everything else in between. Stressors that the respondents have direct contact with tend to be the most important to them. This approach of using focus groups is a critical first step in helping natural resource managers such as Trustees and NGOs understand what subsequent steps to take and develop policy measures that are of most interest and value to the public. Skipping or glossing over this key first task could lead to difficulties with respect to survey design and model development in a non-market valuation study. The focus group results show that concern related to pollution and contamination is much higher than for any of the others. It is thus clear that outreach programs may be necessary to educate the public about the severity of some low-ranked stressors including climate change.     

Action-based feature representation for reverse engineering trading strategies

This paper considers the problem of reverse engineering strategies for trading in the financial markets. We investigate this problem in the context of a trading tournament in which student teams used delta hedging and other mechanisms to attempt to achieve benchmark performance in managing a hedge fund in a simulated market. Our hypothesis is that machine learning models can be trained to solve the apprenticeship learning problem; that is, these models can learn to trade like tournament participants. After reviewing classical return-matching approaches and recent work in inverse reinforcement learning, we propose a supervised learning methodology that makes use of recursive partitioning (RP). Our proposed RP approach is based on a feature representation for actions that, we argue, corresponds to the information structures readily available to tournament participants. RP achieves high accuracy in predicting the type and scale of participant trades and in tracking overall portfolio performance. Our results suggest that further research on our proposed approach is warranted and should include an expansion to testing on data from real markets.