Combining and aggregating environmental data for status and trend assessments: challenges and approaches

Maas-Hebner, Kathleen G.; Harte, Michael; Molina, Nancy; Hughes, Robert M.; Schreck, Carl B.; Yeakley, J. Alan

doi:10.1007/s10661-015-4504-8

Cited by 22 publications

(18 citation statements)

References 86 publications

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“…multiple river basins, regions). These developments have generated significant issues around data type, access, compatibility and analysis (Maas‐Hebner et al., ; Webb, Arthington, & Olden, ). Recent growth of Web‐based data repositories offers huge potential to combine data sets from different sources and regions (e.g.…”

Section: Developments In Environmental Flows Science and Modellingmentioning

confidence: 99%

Recent advances in environmental flows science and water management—Innovation in the Anthropocene

et al. 2018

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The implementation of environmental flow regimes offers a promising means to protect and restore riverine, wetland and estuarine ecosystems, their critical environmental services and cultural/societal values. This Special Issue expands the scope of environmental flows and water science in theory and practice, offering 20 papers from academics, agency researchers and non‐governmental organisations, each with fresh perspectives on the science and management of environmental water allocations. Contributions confront the grand challenge for environmental flows and water management in the Anthropocene—the urgent need for innovations that will help to sustain the innate resilience of social–ecological systems under dynamic and uncertain environmental and societal futures. Basin‐scale and regional assessments of flow requirements mark a necessary advance in environmental water science in the face of rapid changes in water‐resource management activities worldwide (e.g. increases in dams, diversions, retention and reuse). Techniques for regional‐scale hydrological and ecohydrological modelling support ecological risk assessment and identification of priority flow management and river restoration actions. Changing flood–drought cycles, long‐term climatic shifts and associated effects on hydrological, thermal and water quality regimes add enormous uncertainty to the prediction of future ecological outcomes, regardless of environmental water allocations. An improved capacity to predict the trajectories of ecological change in rivers degraded by legacies of past impact interacting with current conditions and future climate change is essential. Otherwise, we risk unrealistic expectations from restoration of river and estuarine flow regimes. A more robust, dynamic and predictive approach to environmental water science is emerging. It encourages the measurement of process rates (e.g. birth rate, colonisation rate) and species traits (e.g. physiological requirements, morphological adaptations) as well as ecosystem states (e.g. species richness, assemblage structure), as the variables representing ecological responses to flow variability and environmental water allocations. Another necessary development is the incorporation of other environmental variables such as water temperature and sedimentary processes in flow–ecological response models. Based on contributions to this Special Issue, several recent compilations and the wider literature, we identify six major scientific challenges for further exploration, and seven themes for advancing the management of environmental water. We see the emerging frontier of environmental flows and water science as urgent and challenging, with numerous opportunities for reinvigorated science and methodological innovation in the expanding enterprise of environmental water linked to ecological sustainability and social well‐being.

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Section: Developments In Environmental Flows Science and Modellingmentioning

confidence: 99%

Recent advances in environmental flows science and water management—Innovation in the Anthropocene

et al. 2018

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“…Imposing further constraints based on the statistical distribution of the response variable may also be necessary to accurately model and predict extreme values. Careful consideration of such stratified sampling approaches is essential (Maas‐Hebner et al ., ). Iteratively conducting modeling and validation with multiple samples could be incorporated into the process within the SSN package in R (Jay Ver Hoef, November 5, 2015, personal communication); however, it is clear from our results that conducting modeling and prediction on a single set of modeling and validation sites can greatly affect the study inferences.…”

Section: Discussionmentioning

confidence: 97%

“…Because of the spatial dependencies among monitoring sites inherently necessary for SSN modeling, the sampling design of such studies influences the statistical analysis approaches that can be adopted (McDonnell et al ., ) and possibly the validity of the inferences made from their results. Using or combining data from probabilistic and targeted (nonprobabilistic) surveys can further complicate analyses and inferences (Maas‐Hebner et al ., ). Thus, careful exploratory data analysis and study design are imperative in SSN modeling applications.…”

Section: Introductionmentioning

confidence: 99%

Improving Predictive Models of In‐Stream Phosphorus Concentration Based on Nationally‐Available Spatial Data Coverages

Scown

McManus

Carson³

et al. 2017

J American Water Resour Assoc

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Spatial data are playing an increasingly important role in watershed science and management. Large investments have been made by government agencies to provide nationally-available spatial databases; however, their relevance and suitability for local watershed applications is largely unscrutinized. We investigated how goodness of fit and predictive accuracy of total phosphorus (TP) concentration models developed from nationally-available spatial data could be improved by including local watershed-specific data in the East Fork of the Little Miami River, Ohio, a 1290 km watershed. We also determined whether a spatial stream network (SSN) modeling approach improved on multiple linear regression (nonspatial) models. Goodness of fit and predictive accuracy were highest for the SSN model that included local covariates, and lowest for the nonspatial model developed from national data. Septic systems and point source TP loads were significant covariates in the local models. These local data not only improved the models but enabled a more explicit interpretation of the processes affecting TP concentrations than more generic national covariates. The results suggest that SSN modeling greatly improves prediction and should be applied when using national covariates. Including local covariates further increases the accuracy of TP predictions throughout the studied watershed; such variables should be included in future national databases, particularly the locations of septic systems.

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“…For example, open and accessible monitoring data allow for more informed characterization of baseline conditions, can add efficiencies to project review processes, can reduce project development costs, and permit a stronger knowledge foundation in subsequent project reviews and decisions (Dubé and Munkittrick 2001;Maas-Hebner et al 2015;Murray et al 2018). This means that any legislated or regulatory requirement must be accompanied by clear articulation of the benefits of data sharing.…”

Section: Open Data To Support Ce Needsmentioning

confidence: 99%

Water Quality Monitoring to Support Cumulative Effects Assessment and Decision Making in the Mackenzie Valley, Northwest Territories, Canada

Wong

Noble

Hanna

2019

Integr Envir Assess & Manag

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Project proponent‐ and government‐led environmental monitoring are required to identify, understand, and manage cumulative effects (CE), yet such monitoring initiatives are rarely mutually supportive. Notwithstanding the need for a more integrated and complementary approach to monitoring, monitoring efforts are often less effective than intended for addressing CE. This paper examines current monitoring programs in the Mackenzie Valley, Northwest Territories, Canada, based on 7 attributes: consistency, compatibility, observability, detectability, adaptability, accessibility, and usability. Results indicate a tenuous link between and across proponent‐led monitoring requirements under project‐specific water licenses and government‐led monitoring of regional baseline conditions. There is some consistency in what is monitored, but data are often incompatible, insufficient to understand baseline change, not transferable across projects or scales, inaccessible to end users, and ultimately unsuitable to understanding CE. Lessons from the Mackenzie Valley highlight the need for improved alignment of monitoring efforts across programs and scales, characterized by a set of common parameters that are most useful for early detection of cumulative change and supporting regulatory decisions at the project scale. This alignment must be accompanied by more open and accessible data for both proponents and regulators, while protecting the sensitivity of proprietary information. Importantly, there must be conceptual guidance for CE, such that the role of monitoring is clear, providing the types of CE questions to be asked, identifying the hypotheses to be tested, and ensuring timely and meaningful results to support regulatory decisions. © 2019 SETAC

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Combining and aggregating environmental data for status and trend assessments: challenges and approaches

Cited by 22 publications

References 86 publications

Recent advances in environmental flows science and water management—Innovation in the Anthropocene

Recent advances in environmental flows science and water management—Innovation in the Anthropocene

Improving Predictive Models of In‐Stream Phosphorus Concentration Based on Nationally‐Available Spatial Data Coverages

Water Quality Monitoring to Support Cumulative Effects Assessment and Decision Making in the Mackenzie Valley, Northwest Territories, Canada

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