Adaptive Management of Bull Trout Populations in the Lemhi Basin

The bull trout Salvelinus confluentus, a stream-living salmonid distributed in drainages of the northwestern United States, is listed as threatened under the Endangered Species Act because of rangewide declines. One proposed recovery action is the reconnection of tributaries in the Lemhi Basin. Past water use policies in this core area disconnected headwater spawning sites from downstream habitat and have led to the loss of migratory life history forms. We developed an adaptive management framework to analyze which types of streams should be prioritized for reconnection under a proposed Habitat Conservation Plan. We developed a Stochastic Dynamic Program that identified optimal policies over time under four different assumptions about the nature of the migratory behavior and the effects of brook trout Salvelinus fontinalis on subpopulations of bull trout. In general, given the current state of the system and the uncertainties about the dynamics, the optimal policy would be to connect streams that are currently occupied by bull trout. We also estimated the value of information as the difference between absolute certainty about which of our four assumptions were correct, and a model averaged optimization assuming no knowledge. Overall there is little to be gained by learning about the dynamics of the system in its current state, although in other parts of the state space reducing uncertainties about the system would be very valuable. We also conducted a sensitivity analysis; the optimal decision at the current state does not change even when parameter values are changed up to 75% of the baseline values. Overall, the exercise demonstrates that it is possible to apply adaptive management principles to threatened and endangered species, but logistical and data availability constraints make detailed analyses difficult

Solution scanning as a key policy tool: Identifying management interventions to help maintain and enhance regulating ecosystem services

The major task of policy makers and practitioners when confronted with a resource management problem is to decide on the potential solution(s) to adopt from a range of available options. However, this process is unlikely to be successful and cost effective without access to an independently verified and comprehensive available list of options. There is currently burgeoning interest in ecosystem services and quantitative assessments of their importance and value. Recognition of the value of ecosystem services to human well-being represents an increasingly important argument for protecting and restoring the natural environment, alongside the moral and ethical justifications for conservation. As well as understanding the benefits of ecosystem services, it is also important to synthesize the practical interventions that are capable of maintaining and/or enhancing these services. Apart from pest regulation, pollination, and global climate regulation, this type of exercise has attracted relatively little attention. Through a systematic consultation exercise, we identify a candidate list of 296 possible interventions across the main regulating services of air quality regulation, climate regulation, water flow regulation, erosion regulation, water purification and waste treatment, disease regulation, pest regulation, pollination and natural hazard regulation. The range of interventions differs greatly between habitats and services depending upon the ease of manipulation and the level of research intensity. Some interventions have the potential to deliver benefits across a range of regulating services, especially those that reduce soil loss and maintain forest cover. Synthesis and applications: Solution scanning is important for questioning existing knowledge and identifying the range of options available to researchers and practitioners, as well as serving as the necessary basis for assessing cost effectiveness and guiding implementation strategies. We recommend that it become a routine part of decision making in all environmental policy areas. © 2014 by the author(s).The research was partly funded by RELU (RES 240-25-006), Arcadia, NERC (Biodiversity and Ecosystem Service Sustainability Directorate, NE/F01614X/1, NE/K001191/1 and NE/J500665/1), SAPES (Multifunctional Agriculture: Harnessing Biodiversity for Sustaining Agricultural Production and Ecosystem Services), and FORMAS (the Swedish Research Council for Environment, Agricultural Sciences and Spatial Planning)

Balancing Detection and Eradication for Control of Epidemics: Sudden Oak Death in Mixed-Species Stands

Culling of infected individuals is a widely used measure for the control of several plant and animal pathogens but culling first requires detection of often cryptically-infected hosts. In this paper, we address the problem of how to allocate resources between detection and culling when the budget for disease management is limited. The results are generic but we motivate the problem for the control of a botanical epidemic in a natural ecosystem: sudden oak death in mixed evergreen forests in coastal California, in which species composition is generally dominated by a spreader species (bay laurel) and a second host species (coast live oak) that is an epidemiological dead-end in that it does not transmit infection but which is frequently a target for preservation. Using a combination of an epidemiological model for two host species with a common pathogen together with optimal control theory we address the problem of how to balance the allocation of resources for detection and epidemic control in order to preserve both host species in the ecosystem. Contrary to simple expectations our results show that an intermediate level of detection is optimal. Low levels of detection, characteristic of low effort expended on searching and detection of diseased trees, and high detection levels, exemplified by the deployment of large amounts of resources to identify diseased trees, fail to bring the epidemic under control. Importantly, we show that a slight change in the balance between the resources allocated to detection and those allocated to control may lead to drastic inefficiencies in control strategies. The results hold when quarantine is introduced to reduce the ingress of infected material into the region of interest

Modeling infectious disease dynamics in the complex landscape of global health.

Despite some notable successes in the control of infectious diseases, transmissible pathogens still pose an enormous threat to human and animal health. The ecological and evolutionary dynamics of infections play out on a wide range of interconnected temporal, organizational, and spatial scales, which span hours to months, cells to ecosystems, and local to global spread. Moreover, some pathogens are directly transmitted between individuals of a single species, whereas others circulate among multiple hosts, need arthropod vectors, or can survive in environmental reservoirs. Many factors, including increasing antimicrobial resistance, increased human connectivity and changeable human behavior, elevate prevention and control from matters of national policy to international challenge. In the face of this complexity, mathematical models offer valuable tools for synthesizing information to understand epidemiological patterns, and for developing quantitative evidence for decision-making in global health

Socializing One Health: an innovative strategy to investigate social and behavioral risks of emerging viral threats

In an effort to strengthen global capacity to prevent, detect, and control infectious diseases in animals and people, the United States Agency for International Development’s (USAID) Emerging Pandemic Threats (EPT) PREDICT project funded development of regional, national, and local One Health capacities for early disease detection, rapid response, disease control, and risk reduction. From the outset, the EPT approach was inclusive of social science research methods designed to understand the contexts and behaviors of communities living and working at human-animal-environment interfaces considered high-risk for virus emergence. Using qualitative and quantitative approaches, PREDICT behavioral research aimed to identify and assess a range of socio-cultural behaviors that could be influential in zoonotic disease emergence, amplification, and transmission. This broad approach to behavioral risk characterization enabled us to identify and characterize human activities that could be linked to the transmission dynamics of new and emerging viruses. This paper provides a discussion of implementation of a social science approach within a zoonotic surveillance framework. We conducted in-depth ethnographic interviews and focus groups to better understand the individual- and community-level knowledge, attitudes, and practices that potentially put participants at risk for zoonotic disease transmission from the animals they live and work with, across 6 interface domains. When we asked highly-exposed individuals (ie. bushmeat hunters, wildlife or guano farmers) about the risk they perceived in their occupational activities, most did not perceive it to be risky, whether because it was normalized by years (or generations) of doing such an activity, or due to lack of information about potential risks. Integrating the social sciences allows investigations of the specific human activities that are hypothesized to drive disease emergence, amplification, and transmission, in order to better substantiate behavioral disease drivers, along with the social dimensions of infection and transmission dynamics. Understanding these dynamics is critical to achieving health security--the protection from threats to health-- which requires investments in both collective and individual health security. Involving behavioral sciences into zoonotic disease surveillance allowed us to push toward fuller community integration and engagement and toward dialogue and implementation of recommendations for disease prevention and improved health security

The epidemiology of hand, foot and mouth disease in Asia: a systematic review and analysis

Hand, foot and mouth disease (HFMD) is a widespread pediatric disease caused primarily by human enterovirus 71 (EV71) and coxsackievirus A16 (CA16).This study reports a systematic review of the epidemiology of HFMD in Asia.PubMed, Web of Science and Google Scholar were searched up to December 2014.Two reviewers independently assessed studies for epidemiologic and serologic information about prevalence and incidence of HFMD against predetermined inclusion/exclusion criteria.Two reviewers extracted answers for eight specific research questions on HFMD epidemiology. The results are checked by three others.HFMD is found to be seasonal in temperate Asia with a summer peak, and in sub-tropical Asia, with spring and fall peaks, but not in tropical Asia; evidence of a climatic role was identified for temperate Japan. Risk factors for HFMD include hygiene, age, gender and social contacts, but most studies were underpowered to adjust rigorously for confounding variables. Both community-level and school-level transmission have been implicated but their relative importance for HFMD is inconclusive. Epidemiologic indices are poorly understood: No supporting quantitative evidence was found for the incubation period of EV71; the symptomatic rate of EV71/CA16 infection was 10% to 71% in four studies; while the basic reproduction number was between 1.1 to 5.5 in three studies. The uncertainty in these estimates inhibits their use for further analysis.Diversity of study designs complicates attempts to identify features of HFMD epidemiology.Knowledge on HFMD remains insufficient to guide interventions such as the incorporation of an EV71 vaccine in pediatric vaccination schedules. Research is urgently needed to fill these gaps

The epidemiology of hand, foot and mouth disease in Asia: a systematic review and analysis

Hand, foot and mouth disease (HFMD) is a widespread pediatric disease caused primarily by human enterovirus 71 (EV71) and coxsackievirus A16 (CA16).This study reports a systematic review of the epidemiology of HFMD in Asia.PubMed, Web of Science and Google Scholar were searched up to December 2014.Two reviewers independently assessed studies for epidemiologic and serologic information about prevalence and incidence of HFMD against predetermined inclusion/exclusion criteria.Two reviewers extracted answers for eight specific research questions on HFMD epidemiology. The results are checked by three others.HFMD is found to be seasonal in temperate Asia with a summer peak, and in sub-tropical Asia, with spring and fall peaks, but not in tropical Asia; evidence of a climatic role was identified for temperate Japan. Risk factors for HFMD include hygiene, age, gender and social contacts, but most studies were underpowered to adjust rigorously for confounding variables. Both community-level and school-level transmission have been implicated but their relative importance for HFMD is inconclusive. Epidemiologic indices are poorly understood: No supporting quantitative evidence was found for the incubation period of EV71; the symptomatic rate of EV71/CA16 infection was 10% to 71% in four studies; while the basic reproduction number was between 1.1 to 5.5 in three studies. The uncertainty in these estimates inhibits their use for further analysis.Diversity of study designs complicates attempts to identify features of HFMD epidemiology.Knowledge on HFMD remains insufficient to guide interventions such as the incorporation of an EV71 vaccine in pediatric vaccination schedules. Research is urgently needed to fill these gaps

Using Quantitative Disease Dynamics as a Tool for Guiding Response to Avian Influenza in Poultry in the United States of America

Wild birds are the primary source of genetic diversity for influenza A viruses that eventually emerge in poultry and humans. Much progress has been made in the descriptive ecology of avian influenza viruses (AIVs), but contributions are less evident from quantitative studies (e.g., those including disease dynamic models). Transmission between host species, individuals and flocks has not been measured with sufficient accuracy to allow robust quantitative evaluation of alternate control protocols. We focused on the United States of America (USA) as a case study for determining the state of our quantitative knowledge of potential AIV emergence processes from wild hosts to poultry. We identified priorities for quantitative research that would build on existing tools for responding to AIV in poultry and concluded that the following knowledge gaps can be addressed with current empirical data: (1) quantification of the spatio-temporal relationships between AIV prevalence in wild hosts and poultry populations, (2) understanding how the structure of different poultry sectors impacts within-flock transmission, (3) determining mechanisms and rates of between-farm spread, and (4) validating current policy-decision tools with data. The modeling studies we recommend will improve our mechanistic understanding of potential AIV transmission patterns in USA poultry, leading to improved measures of accuracy and reduced uncertainty when evaluating alternative control strategies