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At least 1,603 records · Page 89Linked to original sources
USGS2016

Modelling with stakeholders - Next generation

This paper updates and builds on ‘Modelling with Stakeholders’ Voinov and Bousquet, 2010 which demonstrated the importance of, and demand for, stakeholder participation in resource and environmental modelling. This position paper returns to the concepts of that publication and reviews the progress made since 2010. A new development is the wide introduction and acceptance of social media and web applications, which dramatically changes the context and scale of stakeholder interactions and participation. Technology advances make it easier to incorporate information in interactive formats via visualization and games to augment participatory experiences. Citizens as stakeholders are increasingly demanding to be engaged in planning decisions that affect them and their communities, at scales from local to global. How people interact with and access models and data is rapidly evolving. In turn, this requires changes in how models are built, packaged, and disseminated: citizens are less in awe of experts and external authorities, and they are increasingly aware of their own capabilities to provide inputs to planning processes, including models. The continued acceleration of environmental degradation and natural resource depletion accompanies these societal changes, even as there is a growing acceptance of the need to transition to alternative, possibly very different, life styles. Substantive transitions cannot occur without significant changes in human behaviour and perceptions. The important and diverse roles that models can play in guiding human behaviour, and in disseminating and increasing societal knowledge, are a feature of stakeholder processes today.

Environmental Modelling and Software↗
USGS2021

Supporting cost-effective watershed management strategies for Chesapeake Bay using a modeling and optimization framework

Extensive efforts to adaptively manage nutrient pollution rely on Chesapeake Bay Program's (Phase 6) Watershed Model, called Chesapeake Assessment Scenario Tool (CAST), which helps decision-makers plan and track implementation of Best Management Practices (BMPs). We describe mathematical characteristics of CAST and develop a constrained nonlinear BMP-subset model, software, and visualization framework. This represents the first publicly available optimization framework for exploring least-cost strategies of pollutant load control for the United States' largest estuary . The optimization identifies implementation options for a BMP subset modeled with load reduction effectiveness factors, and the web interface facilitates interactive exploration of >30,000 solutions organized by objective, nutrient control level, and for ~200 counties. We assess framework performance and demonstrate modeled cost improvements when comparing optimization-suggested proposals with proposals inspired by jurisdiction plans. Stakeholder feedback highlights the framework's current utility for investigating cost-effective tradeoffs and its usefulness as a foundation for future analysis of restoration strategies.

Chesapeake Bay watershed↗
USGS2024

When do we need multiple infectious disease models? Agreement between projection rank and magnitude in a multi-model setting

Mathematical models are useful for public health planning and response to infectious disease threats. However, different models can provide differing results, which can hamper decision making if not synthesized appropriately. To address this challenge, multi-model hubs convene independent modeling groups to generate ensembles, known to provide more accurate predictions of future outcomes. Yet, these hubs are resource intensive, and how many models are sufficient in a hub is not known. Here, we compare the benefit of predictions from multiple models in different contexts: (1) decision settings that depend on predictions of quantitative outcomes (e.g., hospital capacity planning), where assessments of the benefits of multi-model ensembles have largely focused; and (2) decisions settings that require the ranking of alternative epidemic scenarios (e.g., comparing outcomes under multiple possible interventions and biological uncertainties). We develop a mathematical framework to mimic a multi-model prediction setting, and use this framework to quantify how frequently predictions from different models agree. We further explore multi-model agreement using real-world, empirical data from 14 rounds of U.S. COVID-19 Scenario Modeling Hub projections. Our results suggest that the value of multiple models could be different in different decision contexts, and if only a few models are available, focusing on the rank of alternative epidemic scenarios could be more robust than focusing on quantitative outcomes. Although additional exploration of the sufficient number of models for different contexts is still needed, our results indicate that it may be possible to identify decision contexts where it is robust to rely on fewer models, a finding that can inform the use of modeling resources during future public health crises.

Epidemics↗
USGS2006

A method for landscape analysis of forestry guidelines using bird habitat models and the Habplan harvest scheduler

Wildlife-habitat relationship models have sometimes been linked with forest simulators to aid in evaluating outcomes of forest management alternatives. However, linking wildlife-habitat models with harvest scheduling software would provide a more direct method for assessing economic and ecological implications of alternative harvest schedules in commercial forest operations. We demonstrate an approach for frontier analyses of wildlife benefits using the Habplan harvest scheduler and spatially explicit wildlife response models in the context of operational forest planning. We used the Habplan harvest scheduler to plan commercial forest management over a 40-year horizon at a landscape scale under five scenarios: unmanaged, an unlimited block-size option both with and without riparian buffers, three cases with different block-size restrictions, and a set-asides scenario in which older stands were withheld from cutting. The potential benefit to wildlife was projected based on spatial models of bird guild richness and species probability of detection. Harvested wood volume provided a measure of scenario costs, which provides an indication of management feasibility. Of nine species and guilds, none appeared to benefit from 50 m riparian buffers, response to an unmanaged scenario was mixed and expensive, and block-size restrictions (maximum harvest unit size) provided no apparent benefit and in some cases were possibly detrimental to bird richness. A set-aside regime, however, appeared to provide significant benefits to all species and groups, probably through increased landscape heterogeneity and increased availability of older forest. Our approach shows promise for evaluating costs and benefits of forest management guidelines in commercial forest enterprises and improves upon the state of the art by utilizing an optimizing harvest scheduler as in commercial forest management, multiple measures of biodiversity (models for multiple species and guilds), and spatially explicit wildlife response models. ?? 2006 Elsevier B.V. All rights reserved.

Forest Ecology and Management↗
USGS2018

Identifying management-relevant research priorities for responding to disease-associated amphibian declines

A research priority can be defined as a knowledge gap that, if resolved, identifies the optimal course of conservation action. We (a group of geographically distributed and multidisciplinary research scientists) used tools from nominal group theory and decision analysis to collaboratively identify and prioritize information needs within the context of disease-associated amphibian decline , in order to develop a strategy that would support US management agency needs. We developed iterated influence diagrams to create and assess a unified research strategy. We illustrated a transparent process for identifying specific knowledge gaps in amphibian disease ecology relevant to environmental management, and then constructed a research plan to address these uncertainties. The resulting priorities include a need to: (1) understand the drivers of the community-disease relationship, (2) determine the mechanisms by which exposure to contaminants influence disease outcomes, (3) identify elements of terrestrial and aquatic habitats that stabilize host-pathogen dynamics, (4) discuss how metapopulations may be managed to reduce the speed and intensity of disease outbreaks, and (5) define the relationship between habitat management and the environmental and host microbiomes. Along with identifying research priorities for disease management, we present the details of the process used to develop a consensus plan for addressing disease-related declines in amphibians on federally managed lands of the United States.

Global Ecology and Conservation↗
USGS2021

Resilience to fire and resistance to annual grass invasion in sagebrush ecosystems of US National Parks

Western North American sagebrush shrublands and steppe face accelerating risks from fire-driven feedback loops that transition these ecosystems into self-reinforcing states dominated by invasive annual grasses. In response, sagebrush conservation decision-making is increasingly done through the lens of resilience to fire and annual grass invasion resistance. Operationalizing resilience and resistance concepts requires place-based understanding of resilience and resistance variation among landscapes over time. Place-based insights allow for landscape prioritization in targeted areas of significance such as protected-area sagebrush ecosystems that exhibit inherently low resilience and are therefore at high risk of loss. We used a multi-scale approach to evaluate sagebrush resiliency and strategic planning across 1) the US National Park system, 2) a regional suite of five parks, and 3) for two specific park case studies. First, we summarized broad patterns of relative resilience to fire and resistance to annual grass invasion across all parks with sagebrush ecosystems. We found that national parks represented ~11% of US protected-area sagebrush ecosystems and reflected a similar low-resilience bias that occurs across the biome, broadly. Climate change is likely to shift both low- and high-resilience park sagebrush ecosystems towards moderate resiliency, creating new opportunities and constraints for park conservation. Approximately seventy park units include at least some sagebrush shrublands or steppe, but we identified 40 parks with substantial amounts (>20% of park area) that can be included in an agency-wide conservation strategy. Second, we examined detailed patterns of resilience and resistance, fire history and fire risk, cheatgrass ( Bromus tectorum ) invasion, and sagebrush shrub ( Artemisia spp.) persistence in five national park units in Columbia Basin and Snake River Plain sagebrush steppe, contextualized by the broader summary. In these five parks, fire frequency and size increased in recent decades. Cheatgrass invasion and sagebrush persistence correlated strongly with resilience, burn frequency (0–3 fires since ~1940), and burn probability, but with important variation, in part mediated by local-scale topography. Third, we used these insights to assemble strategic sagebrush ecosystem fire protection mapping scenarios in two additional parks – Lava Beds National Monument and Great Basin National Park. Readily available and periodically updated geospatial data including soil surveys, fire histories, vegetation inventories, and long-term monitoring support resiliency-based adaptive management through tactical planning of pre-fire protection, post-fire restoration, and triage. Our assessment establishes the precarious importance of the US national park system to sagebrush ecosystem conservation and an operational strategy for place-based and science-supported conservation.

Arizona, California, Colorado, Idaho, Montana, New↗
USGS2025

A generalized design flood estimation framework under stationary and non-stationary scenarios

With the ever-ongoing debate over the death of stationarity in flood time series, developing methods for flood frequency analysis that can address both stationarity and non-stationarity simultaneously has become increasingly important for design flood estimation. Existing non-stationary flood frequency analysis (NFFQ) methods are either limited to providing time-varying conditional flood quantile estimates or lack closed-form expression to estimate the design flood over the planning period. We propose a novel framework, MM-NFFQ, that introduces marginal moments (MM) estimation techniques to provide a closed-form expression to estimate design flood under non-stationarity. We demonstrate MM-NFFQ using the LP3 distribution for estimating conditional moments, but in principle, it can work for any 3-parameter distribution. We first show the proposed MM-NFFQ collapses to stationary flood frequency analysis analytically using synthetic data and then demonstrate the MM-NFFQ approach for two basins exhibiting non-stationarity in their flood time series. We further extend the analysis to selected 40 basins across CONUS and find that arid basins exhibit higher deviation from stationarity. Thus, the proposed MM-NFFQ framework can estimate traditional flood frequency curves for both, stationary and non-stationary flood processes, and can also be utilized to analyze the changes in conditional moments and marginal moments over different planning horizons.

Journal of Hydrology X↗
USGS2026

Mars as one system: Insights from the 8th international conference on Mars polar science and exploration

The 8th International Conference on Mars Polar Science and Exploration (ICMPSE) provided new insights into the complex interplay between Martian ice, climate, and atmospheric dynamics. The conference emphasized a holistic view of Mars as a system, where surface processes, subsurface ice, atmospheric dynamics, and historical climate shifts are interconnected. Research updates spanned cutting-edge remote sensing techniques and observations, terrestrial analog studies, and theoretical modeling, providing a multidimensional view of Mars' dynamic history and present-day activity. Numerous presentations highlighted the importance of understanding Mars as an integrated and dynamic system where surface and atmospheric processes interact over various timescales. This paper synthesizes unresolved questions and the major themes discussed, including mid-latitude glaciation, the evolution of the polar layered deposits (PLDs), terrestrial analog studies, climate modeling, and future mission planning. The findings contributed to refining models of Martian climate history, assessing the potential for extant life, and planning future human exploration. We also discuss the historical perspective of Mars Polar Science and new findings since the 7th conference in this series and anticipate the next four to 20 years of science on Mars related to ice, climate, and the atmosphere.

Icarus↗
USGS2020

Variations in community evacuation potential related to average return periods in probabilistic tsunami hazard analysis

Tsunami risk management requires strategies that can address multiple sources with different recurrence intervals, wave-arrival times, and inundation extents. Probabilistic tsunami hazard analysis (PTHA) provides a structured way to integrate multiple sources, including the uncertainties due to the natural variability and limited knowledge of sources. PTHA-based products relate to specific average return periods (ARP) and while there has been considerable attention paid to ARP choice for building codes, guidance on ARP choice to support evacuation planning and related land use is lacking. We use the State of California (USA) coastal communities as a case study to explore the use of geospatial analysis and pedestrian-evacuation modeling for comparing the societal implications of tsunamis based on evacuation areas that reflect inundation from 475-year, 975-year, and 2475-year ARPs. Results demonstrate that changes in PTHA ARP had a substantial effect on the number of tax-lot parcels in PTHA evacuation areas, but not on the primary land use of these parcels or which communities had the largest number of exposed parcels. Composite PTHA maps provided high-level insights on hazard exposure and identified dominant sources; however, disaggregated PTHA outputs that reflect single source parameters (e.g., wave-arrival time) were necessary to quantify evacuation potential from local and distant tsunamis. Framing changes in ARP assumption based on changes in the number, land-use type, and potential evacuation challenges of parcels in evacuation areas can provide valuable insight on the real-world implications of which ARP to use in land use or evacuation planning.

California↗
USGS2010

Comparing forest fragmentation and its drivers in China and the USA with Globcover v2.2

Forest loss and fragmentation are of major concern to the international community, in large part because they impact so many important environmental processes. The main objective of this study was to assess the differences in forest fragmentation patterns and drivers between China and the conterminous United States (USA). Using the latest 300-m resolution global land cover product, Globcover v2.2, a comparative analysis of forest fragmentation patterns and drivers was made. The fragmentation patterns were characterized by using a forest fragmentation model built on the sliding window analysis technique in association with landscape indices. Results showed that China’s forests were substantially more fragmented than those of the USA. This was evidenced by a large difference in the amount of interior forest area share, with China having 48% interior forest versus the 66% for the USA. China’s forest fragmentation was primarily attributed to anthropogenic disturbances, driven particularly by agricultural expansion from an increasing and large population, as well as poor forest management practices. In contrast, USA forests were principally fragmented by natural land cover types. However, USA urban sprawl contributed more to forest fragmentation than in China. This is closely tied to the USA’s economy, lifestyle and institutional processes. Fragmentation maps were generated from this study, which provide valuable insights and implications regarding habitat planning for rare and endangered species. Such maps enable development of strategic plans for sustainable forest management by identifying areas with high amounts of human-induced fragmentation, which improve risk assessments and enable better targeting for protection and remediation efforts. Because forest fragmentation is a long-term, complex process that is highly related to political, institutional, economic and philosophical arenas, both nations need to take effective and comprehensive measures to mitigate the negative effects of forest loss and fragmentation on the existing forest ecosystems.

Journal of Environmental Management↗
USGS2011

A framework for sustainable invasive species management: environmental, social and economic objectives

Applying the concept of sustainability to invasive species management (ISM) is challenging but necessary, given the increasing rates of invasion and the high costs of invasion impacts and control. To be sustainable, ISM must address environmental, social, and economic factors (or *pillars*) that influence the causes, impacts, and control of invasive species across multiple spatial and temporal scales. Although these pillars are generally acknowledged, their implementation is often limited by insufficient control options and significant economic and political constraints. In this paper, we outline specific objectives in each of these three *pillars* that, if incorporated into a management plan, will improve the plan's likelihood of sustainability. We then examine three case studies that illustrate how these objectives can be effectively implemented. Each pillar reinforces the others, such that the inclusion of even a few of the outlined objectives will lead to more effective management that achieves ecological goals, while generating social support and long-term funding to maintain projects to completion. We encourage agency directors and policy-makers to consider sustainability principles when developing funding schemes, management agendas, and policy.

Journal of Environmental Management↗
USGS2019

Assessment of site-specific agricultural Best Management Practices in the Upper East River watershed, Wisconsin, using a field-scale SWAT model

The Great Lakes “Priority Watershed” effort targeted the Upper East River watershed, a 116.5 km2 tributary watershed to Green Bay in Wisconsin, to reduce sediment and nutrients entering Green Bay. A Soil and Water Assessment Tool (SWAT) model was created to determine the effectiveness of Best Management Practices (BMPs) derived from the U.S. Department of Agriculture-Natural Resources Conservation Service National Conservation Planning (NCP) Database. The model was calibrated at the monthly timestep for flow, sediment, dissolved reactive phosphorus (DRP), total phosphorus (TP), and total nitrogen (TN). Field- and watershed-scale sediment and nutrient reductions were calculated due to the implementation of 74 BMP combinations on dairy and cash grain rotations. Modeling results indicated that when multiple BMPs are placed on a field, especially those that included filter strips and grassed waterways, generally reduced sediment and nutrient loads more than a single BMP implementation. The most effective in-field practice at reducing DRP and TP on dairy fields was a combination of 5 different BMPs: cover crops, crop rotation, nutrient management plan, reduced tillage, and a filter strip. Conservation cover was the most effective practice at reducing sediment and nutrient yields. Sediment and nutrient loads decreased at the watershed scale as the quantity and coverage of BMPs increased. When all contracted NCP BMPs were simulated at the watershed scale, sediment loads were reduced 2%, while TP, DRP, TN and nitrate loads were reduced 20%, 9%, 24%, and 17%, respectively. Modeling scenarios indicated that as the number and area of BMPs were increased, sediment and nutrient load reductions were also increased.

Wisconsin↗
USGS2021

A renewed philosophy about supplemental sea lamprey controls

Invasive sea lamprey ( Petromyzon marinus ) populations in the Laurentian Great Lakes have been reduced by up to 90% through the use of selective pesticides (lampricides) and physical sea lamprey barriers that block spawning migrations. Nevertheless, other control methods are needed to achieve integrated pest management objectives, delay biological resistance, and address societal pressure to reduce pesticide use and restore lotic connectivity through dam removals. Despite decades of research and scientific advances, new control tools that focus on controlling adult and juvenile life stages have been rare because tactics have not been cost-effective alternatives to lampricides and sea lamprey barriers. Here, we propose a renewed philosophy highlighting that new control methods need not be true alternatives to lampricides and sea lamprey barriers (i.e., have similar effectiveness), but instead can be useful as supplemental controls integrated with current methods, especially in places where current methods are less effective due to environmental or societal conditions. Current case studies pairing multiple supplemental controls together on two Lake Huron tributaries, the Black Mallard and Cheboygan Rivers, have shown promise in reducing sea lamprey reproductive success, the scope of lampricide treatments, and ultimately the number of juvenile sea lampreys produced. Additional case studies are planned and will be evaluated within a decade-long adaptive assessment plan.

Journal of Great Lakes Research↗
USGS2021

Evaluating low flow patterns, drivers and trends in the Delaware River Basin

In the humid, temperate Delaware River Basin (DRB) where water availability is generally reliable, summer low flows can cause competition between various human and ecological water uses. As temperatures continue to rise, population increases and development expands, it is critical to understand historical low flow variability to anticipate and plan for future flows. Using a sample of 325 U.S. Geological Survey gages, we evaluated spatial patterns in several low flow metrics, the biophysical and climatic drivers of these metrics, and trends in low flows for two periods: 1950-2018 and 1980-2018. We calculated the annual 7-day low flow and date, low flow deficit as the departure below a long-term daily flow threshold and the number of discrete low flow periods below this threshold. We also aggregated several climate metrics to watershed scale and used existing watershed properties quantifying land cover, topography, soils, geology, and human activity. Random forest models were used to assess the hierarchy of variable importance in explaining mean-annual low flow variability for each low flow metric using all gages. We find muted regional patterns in mean-annual low flow and low flow variability, likely due to the myriad of anthropogenic, landscape, and flow modifications that obscure flow regimes from their natural characteristics. In contrast, individual years show markedly different spatial patterns in low flow magnitude and severity. Coincident with increases in precipitation, 7-day low flows have generally increased and low flow deficits decreased for both 1950-2018 and 1980-2018 periods. However, 7-day low flows have decreased in the Coastal Plain physiographic province where water use and impervious area have increased in recent decades, highlighting the effects of land and water management on low flows. With continued change expected in the DRB, additional research needs are highlighted to enable estimation of future low flows and to plan for periods of prolonged low flow.

Delaware, New Jersey, New York, Pennsylvania↗
USGS2026

Deep learning error post-processing improves stochastic watershed modeling

Hydrologic extremes, including floods and droughts, pose substantial societal risks that are expected to intensify with climate change. Deterministic watershed models (DWMs) remain a mainstay for modeling these extremes, but lack explicit representation of uncertainty, limiting their utility for risk-informed planning. Stochastic watershed models (SWMs) address this limitation by generating ensembles of streamflow via models of observed DWM residuals. However, most SWMs struggle with the complex dependence between DWM residuals and the underlying hydrologic state, which can complicate stochastic simulations under nonstationary climates. Deep learning (DL) models, whether used as standalone models or post-processors for process-based DWMs, offer a pathway to address this challenge by reducing conditional dependence. In this study, we evaluate SWMs applied to seven models: three process-based models (PRMS, Hymod, and HBV), their hybrid process-DL counterparts, and a pure DL DWM, focusing on daily simulations and extremes under both historical conditions and synthetic climate change scenarios. Results for a case study watershed in Massachusetts show that SWMs applied to hybrid or pure DL DWMs consistently outperform those applied to process-based DWMs. However, an SWM applied to the pure DL model exhibits weaknesses at low flows for this study basin, underscoring the value of hybrid approaches. Extending the analysis across 73 additional basins demonstrates that these improvements are robust and generalizable statewide. This work highlights the potential of a DL-enhanced stochastic watershed modeling framework to advance hydrologic risk prediction under changing climate conditions, offering a scalable methodology for integrating uncertainty into watershed modeling for long-term planning.

Journal of Hydrology↗
USGS2017

Reply to: Terry, J. and Goff, J. comment on “Late Cenozoic sea level and the rise of modern rimmed atolls” by Toomey et al. (2016), Palaeogeography, Palaeoclimatology, Palaeoecology 4 51: 73–83.

We appreciate Terry and Goff's thoughtful comment in response to our proposed atoll development model. Flank collapse of reef-built slopes likely does affect plan-form atoll morphology in some locations and potentially poses a tsunami hazard to low-lying Pacific islands (Terry and Goff, 2013). However, given the often rapid rates of lagoon infill (> 1 mm/yr; Montaggioni, 2005), such failure events would likely need to be frequent and widespread in order to leave a morphologic imprint on modern western Pacific atoll lagoon depths. Few atoll flank collapse features have been dated but many of the arcuate bight-like structures (ABLS) identified could be inherited from scars incised into the initial volcanic edifice (e.g. Terry and Goff, 2013 and refs. therein) — submarine mass wasting has been extensively documented on young hotspot islands (e.g. Hawaiian Islands: Moore et al., 1989; Reunion: Oehler et al., 2008). Atolls in the Marshall Islands, where our main study site Enewetak Atoll is located, are likely ~ 50–100 million years old (Larson et al., 1995) and dating of adjacent deep-water turbidite aprons in the Nauru Basin (DSDP Site 462; Schlanger and Silva, 1986) suggests that large atoll flank collapse events have been relatively infrequent there since the mid-Miocene (< 11 Ma). In our simple, 1D atoll development model (Toomey et al., 2016a), we included the minimum set of processes (vertical accretion, dissolution, and lagoonal infilling) required to accurately simulate Enewetak's ‘recent’ depositional history (8.5–0 Ma) and explain basic differences in lagoon depth among western Pacific atolls. We agree future development of a model incorporating the wider range of processes impacting connectivity between reef-bound lagoons and the ocean (e.g. Ouillon et al., 2004; Toomey et al., 2016b), including stochastic mass wasting events, will be essential for exploring the plan-form and 3D shapes of atolls. To our knowledge, no quantitative model of long-term atoll development has explicitly linked lagoon restriction/sedimentation to episodic flank collapse events (e.g. Montaggioni et al., 2015; Paterson et al., 2006; Quinn, 1991; Warrlich et al., 2002). Testing Terry and Goff's proposed conceptual model for how rim failure processes affect atoll morphology in a numerical context will require deep drilling along arcuate bight-like structures, as well as adjacent, unaffected, rim and lagoon areas, in order quantify how often failures occur and how quickly the rim/lagoon is rebuilt afterwards. The model we present here provides a general framework capable of integrating atoll flank collapse processes once they are sufficiently constrained by such observational datasets.

Palaeogeography, Palaeoclimatology, Palaeoecology↗
USGS2004

Scientific objectives and selection of targets for the SMART-1 Infrared Spectrometer (SIR)

The European SMART-1 mission to the Moon, primarily a testbed for innovative technologies, was launched in September 2003 and will reach the Moon in 2005. On board are several scientific instruments, including the point-spectrometer SMART-1 Infrared Spectrometer (SIR). Taking into account the capabilities of the SMART-1 mission and the SIR instrument in particular, as well as the open questions in lunar science, a selection of targets for SIR observations has been compiled. SIR can address at least five topics: (1) Surface/regolith processes; (2) Lunar volcanism; (3) Lunar crust structure; (4) Search for spectral signatures of ices at the lunar poles; and (5) Ground truth and study of geometric effects on the spectral shape. For each topic we will discuss specific observation modes, necessary to achieve our scientific goals. The majority of SIR targets will be observed in the nadir-tracking mode. More than 100 targets, which require off-nadir pointing and off-nadir tracking, are planned. It is expected that results of SIR observations will significantly increase our understanding of the Moon. Since the exact arrival date and the orbital parameters of the SMART-1 spacecraft are not known yet, a more detailed planning of the scientific observations will follow in the near future. ?? 2004 Elsevier Ltd. All rights reserved.

Planetary and Space Science↗
USGS2020

Modeling pathogen dispersal in marine fish and shellfish

Bio-physical models are a useful tool for understanding dispersal and transmission of marine pathogens. While utilized for larval dispersal models, they are only recently being used in epidemiological studies and are currently underutilized by the marine epidemiology field. Bio-physical models are useful for spatial planning and coastal management. For example, they have been used for spatial planning of salmon farm site locations, and to establish early warning networks. Bio-physical modeling can be used to test hypotheses, rather than simply develop them. Model resolution and computation demands must be balanced when making decisions about model parameters. Epidemiological bio-physical models are in their infancy. While they have proven useful so far, future applications of these models can incorporate more aspects of disease dynamics and address many additional questions.

Trends in Parasitology↗