Lessons learned and recommendations in conducting solutions-driven environmental and public health research.

Solutions-driven research is a transdisciplinary approach that incorporates diverse forms of expertise to identify solutions to stakeholder-identified environmental problems. This qualitative evaluation of early solutions-driven research projects provides transferable recommendations to improve researcher and stakeholder experiences and outcomes in transdisciplinary environmental research projects. Researchers with the U.S. Environmental Protection Agency (EPA) Office of Research and Development recently piloted a solutions-driven research approach in two parallel projects; one addressing nutrient management related to coastal waters and another studying wildland fire smoke impacts on indoor air quality. Studying the experiences of those involved with these pilots can enhance the integration of researcher and experiential expertise, improving solutions-driven research outcomes. Data collection included semi-structured interviews with 17 EPA researchers and 12 other stakeholders and reflective case narratives from the authors. We used conventional content analysis to qualitatively analyze perspectives on implementing innovative engagement and research approaches in a solutions-driven process. Findings that reflect common perspectives include the importance of continuous engagement, the challenges of differing timelines and priorities for researchers and stakeholders, and the need to define consistent markers of success across researchers and stakeholders. Key lessons to improve transdisciplinary research identified from the analysis are (1) improving clarity of roles and responsibilities; (2) planning to provide sufficient, continuous project funding over multiple years; (3) expecting research needs and plans to adapt to evolving circumstances; and (4) clearly defining the end of the project.

Surveillance for second breast cancer events in women with a personal history of breast cancer using breast MRI: a systematic review and meta-analysis.

PURPOSE: Women with personal history of breast cancer (PHBC) are currently recommended to receive annual mammography for surveillance of breast cancer recurrence or new primary. However, given issues in accuracy with mammography, there is a need for evolving evidence-based surveillance recommendations with supplemental imaging. In this systematic review, we compiled and compared existing studies that describe the test performance of surveillance breast MRI among women with PHBC. METHODS: We searched PubMed and EMBASE using MeSH terms for studies (2000-2019) that described the diagnostic characteristics of breast MRI in women with PHBC. Search results were reviewed and included based on PICOTS criteria; quality of included articles was assessed using QUADAS-2. Meta-analysis of single proportions was conducted for diagnostic characteristics of breast MRI, including tests of heterogeneity. RESULTS: Our review included 11 articles in which unique cohorts were studied, comprised of a total of 8338 women with PHBC and 12,335 breast MRI done for the purpose of surveillance. We predict intervals (PI) for cancer detection rate per 1000 examinations (PI 9-15; I2 = 10%), recall rate (PI 5-31%; I2 = 97%), sensitivity (PI 58-95%; I2 = 47%), specificity (PI 76-97%; I2 = 97%), and PPV3 (PI 16-40%; I2 = 44%). CONCLUSIONS: Studies addressing performance of breast MRI are variable and limited in population-based studies. The summary of evidence to date is insufficient to recommend for or against use of breast MRI for surveillance among women with PHBC.

Structured Decision Making to Meet a National Water Quality Mandate.

Water quality criteria are necessary to ensure protection of ecological and human health conditions, but compliance can require complex decisions. We use structured decision making to consider multiple stakeholder objectives in a water quality management process, with a case study in the Three Bays watershed on Cape Cod, Massachusetts. We set a goal to meet or exceed a nitrogen load reduction target for the watershed and four key objectives: minimizing economic costs of implementing management actions, minimizing the complexity of permitting management actions, maximizing stakeholder acceptability of the management actions, and maximizing the provision of ecosystem services (recreational opportunity, erosion and flood control, socio-cultural amenity). We used multi-objective optimization and sensitivity analysis to generate many possible solutions that implement different combinations of nitrogen-removing management actions and reflect tradeoffs between the objectives. Results show that technological advances in controlling household nitrogen sources could provide lower cost solutions and positive impacts to ecosystem services. Although this approach is demonstrated with Cape Cod data, the decision-making process is not specific to any watershed and could be easily applied elsewhere.

Developing qualitative ecosystem service relationships with the Driver-Pressure-State-Impact-Response framework: A case study on Cape Cod, Massachusetts.

Understanding the effects of environmental management strategies on society and the environment is critical for evaluating their effectiveness, but is often impeded by limited data availability. In this article, we present a method that can help scientists to support resource managers' thinking about social-ecological relationships in coupled human and natural systems. Our method aims to model qualitative cause-effect relationships between management strategies and ecosystem services, using information provided by knowledgeable participants, and the tradeoffs between strategies. Social, environmental, and cultural indicators are organized using the Driver-Pressure-State-Impact-Response, or DPSIR, framework. The relationships between indicators are evaluated using a decision tree and numerical representations of interaction strength. We use a matrix multiplication procedure to model direct and indirect interaction effects, and we provide guidelines for combining effects. Results include several data tables from which information can be visualized to understand the plausible interaction effects of implementing management strategies on ecosystem services. We illustrate our method with a water quality management case study on Cape Cod, Massachusetts.

A resilience framework for chronic exposures: water quality and ecosystem services in coastal social-ecological systems.

Water quality degradation is a chronic problem which influences the resilience of a social-ecological system differently than acute disturbances, such as disease or storms. Recognizing this, we developed a tailored resilience framework that applies ecosystem service concepts to coastal social-ecological systems affected by degraded water quality. We present the framework as a mechanism for coordinating interdisciplinary research to inform long-term community planning decisions pertaining to chronic challenges in coastal systems. The resulting framework connects the ecological system to the social system via ecological production functions and ecosystem services. The social system then feeds back to the ecological system via policies and interventions to address declining water quality. We apply our resilience framework to the coastal waters and communities of Cape Cod (Barnstable County, Massachusetts, USA) which are affected by nitrogen over-enrichment. This approach allowed us to design research to improve the understanding of the effectiveness and acceptance of water quality improvement efforts and their effect on the delivery of ecosystem services. This framework is intended to be transferable to other geographical settings and more generally applied to systems exposed to chronic disturbances in order to coordinate interdisciplinary research planning and inform coastal management.

Evaluating the ecological significance of laboratory response data to predict population-level effects for the estruarine amphipod Ampelisca abdita.

Ten-day acute mortality of the benthic amphipod Ampelisca abdita is used in a number of regulatory, research, and monitoring programs to evaluate chemical contamination of marine sediments. Although this endpoint has proven to be valuable for characterizing the relative toxicities of sediments, the significance of acute mortality with respect to population viability has not yet been established. In this study, population modeling along with empirical extrapolation were used to describe a relationship between acute mortality and population-level response of A. abdita. The research involved the performance of a standard 10-d sediment toxicity bioassay and a 70-d full life-cycle chronic population (including reproduction) bioassay exposing A. abdita to sediments spiked with concentrations of the divalent metal cadmium (normalized to acid volatile sulfide) expected to produce a range of biological effects. These data provided age-specific schedules of survival and fecundity that were used to parameterize an age-classified projection matrix model for A. abdita. Measured exposure data and population growth rate estimates, obtained using the demographic information collected during the 70-d assay, were used to develop exposure-response models. These data were also used to develop an empirical relationship between population growth rate (lambda) and acute mortality. This relationship describes how acute data may be used to predict concentrations that produce population-level effects. Model manipulations permit extrapolation of early life-stage mortality (the acute endpoint) to changes in population growth rate. These relationships were used to evaluate a range of ecologically acceptable acute mortality for A. abdita.

Individual effects of estrogens on a marine fish, Cunner (Tautogolabrus adspersus), extrapolated to the population level.

Endocrine-disrupting chemicals (EDCs) in the environment may alter the population dynamics of wildlife by affecting reproductive output. This study describes a matrix modeling approach to link laboratory studies on endocrine disruption with potential ecological effects. The experimental model used is cunner (Tautogolabrus adspersus), which inhabit estuarine and marine areas where sewage treatment and other discharges containing estrogenic EDCs are likely. To test the effects of estrogenic exposures on fecundity, reproductively active cunner were exposed in three separate experiments by implanting 17beta-estradiol, estrone, or 17alpha-ethynylestradiol subcutaneously in a slow-release matrix at 0.05, 0.5, and 2.5 mg/kg. Egg production per gram female and egg viability were determined daily for a 1-week preexposure period and then for a 2-week exposure period. The mean number of eggs produced per gram female and egg viability (%) were calculated for the initial preexposure period and the 2-week exposure period for each experiment. Significant changes were observed in egg production per gram female in the high-17beta-estradiol treatment (P = 0.07) and high-17alpha-ethynylestradiol treatment (P = 0.04). A significant increase was observed in egg viability (%) in the low-17alpha-ethynylestradiol treatment (39.0%; P < or = 0.05). Cunner population response was projected using an age-structured matrix population model parameterized with published survival and fecundity estimates. By incorporating reproductive response data from laboratory exposures, model projections were used to describe how reproductive changes by estrogen treatment could alter cunner population growth rate (lambda). Published by Elsevier Inc.