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USGS2017

Synthesis of data from high-frequency nutrient and associated biogeochemical monitoring for the Sacramento–San Joaquin Delta, northern California

Executive Summary This report is the second in a series of three reports that provide information about high-frequency (HF) nutrient and biogeochemical monitoring in the Sacramento–San Joaquin Delta of northern California (Delta). The purpose of this report is to synthesize the data available from a nutrient and water-quality HF (about every 15 minutes) monitoring network operated by the U.S. Geological Survey in the northern Delta. In this report, we describe the network and focus on the purpose of each station. We then present and discuss the available data, at various timescales—first at the monthly, seasonal, and inter-annual timescales, and second, for comparison, at the tidal and event timescales. As expected, we determined that there is substantial variability in nitrate-N concentrations at short timescales within hours, but also significant variability at longer timescales such as months or years. Resolving this variability is made possible by the HF data, with the largest variability caused by storms, tides, and diel biological processes. Given this large temporal variability, calculations of cumulative nutrient fluxes (for example, daily, monthly, or annual loads) is difficult without HF data. For example, in the Cache Slough, calculation of the annual load without the tidal variability resulted in a 30 percent underestimation of the true annual load value. We conclude that HF measurements are important for accurate determination of fluxes and loads in tidal environments, but, more importantly, provide important insights into processes and rates of nutrient cycling. This report, along with the other two reports of this series (Bergamaschi and others, 2017; Kraus, Bergamaschi, and others, 2017), was drafted in cooperation with the Delta Regional Monitoring Program to help scientists, managers, and planners understand how HF data improve our understanding of nutrient sources and sinks, drivers, and effects in the Delta. The first report in the series (Kraus, Bergamaschi, and others, 2017) provides an introduction to the reasons for and fundamental concepts behind using HF monitoring measurements, including a brief summary of nutrient status and trends in the Delta and an extensive literature review showing how and where other research and monitoring programs have used HF monitoring to improve our understanding of nutrient cycling. The report covers the various technologies available for HF nutrient monitoring and presents the different ways HF monitoring instrumentation may be used for fixed station and spatial assessments. Finally, it presents numerous examples of how HF measurements are currently (2017) being used in the Delta to examine how nutrients and nutrient cycling are related to aquatic habitat conditions. The third report in the series (Bergamaschi and others, 2017) provides the background, principles, and considerations for designing an HF nutrient-monitoring network for the Delta to address high-priority, nutrient-management questions. The report starts with discussion of the high‑priority management questions to be addressed, continues through discussion of the questions and considerations that place demands and constraints on network design, discusses the principles applicable to network design, and concludes with the presentation of three example nutrient-monitoring network designs for the Delta, proposed to address high-priority questions identified by the Delta Regional Monitoring Program (Delta Regional Monitoring Program Technical Advisory Committee, 2015).

California↗

USGS2012

February 2012 workshop jumpstarts the Mekong Fish Monitoring Network

The Mekong River in Southeast Asia travels through a basin rich in natural resources. The river originates on the northern slope of the world's tallest mountains, the Himalaya Range, and then drops elevation quickly through steep mountain gorges, tumbling out of China into Myanmar (Burma) and the Lao People's Democratic Republic (Lao PDR). The precipitous terrain of Lao PDR and Thailand generates interest in the river and its tributaries for hydropower development. The terrain, soils, water, and climate make it one of the world's most biologically rich regions. The Mekong's bounty is again on display in the Mekong River Delta, where rice production has successfully been increased to high levels making Vietnam second only to Thailand as the world's largest rice exporters. At least 800 fish species contribute to the natural resource bounty of the Mekong River and are the basis for one of the world's most productive fisheries that provide the primary protein source to more than 50 million people. Against this backdrop of rich natural resources, the U.S. Geological Survey (USGS) is working with the consulting firm FISHBIO, colleagues from the international Delta Research and Global Observation Network (DRAGON) Institute, and a broad contingent of Southeast Asian representatives and partners from abroad to increase knowledge of the Mekong River fisheries and to develop the capacity of permanent residents to investigate and understand these fisheries resources. With the Lower Mekong Basin (LMB) region facing the likelihood of significant environmental changes as a result of both human activities and global climate change, enhancing environmental understanding is critical. To encourage cooperation among the LMB scientists and managers in the study of the Mekong River's fisheries, FISHBIO and the USGS, with generous support from the U.S. State Department, hosted a workshop in Phnom Penh, Cambodia, in February 2012. Workshop participants were from Lao PDR, Thailand, Cambodia, and Vietnam. Representatives from the governments, universities, nongovernmental organizations, and the Mekong River Commission discussed current and potential methods and mechanisms of the Mekong Fish Monitoring Network. The goals of the workshop were to determine if the Network and associated databases were of interest and value to the LMB nations, to determine if future fisheries monitoring data would be comparable among the nations, and to establish methods and an organizational structure for collaborating on future monitoring and research. The participants in this international workshop agreed that the Network would be useful but would require additional funding to secure their full participation. The USGS and FISHBIO are collaboratively seeking additional funding to expand research participation and projects in all four LMB nations. If the Network can facilitate cooperation among many fisheries researchers in the LMB, the basin would become a model of cooperative international fishery studies and would increase the understanding of a river basin rich in natural resources.

Phnom Penh↗

USGS2016

Snake fungal disease: An emerging threat to wild snakes

Since 2006, there has been a marked increase in the number of reports of severe and often fatal fungal skin infections in wild snakes in the eastern USA. The emerging condition, referred to as snake fungal disease (SFD), was initially documented in rattlesnakes, where the infections were believed to pose a risk to the viability of affected populations. The disease is caused by Ophidiomyces ophiodiicola , a fungus recently split from a complex of fungi long referred to as the Chrysosporium anamorph of Nannizziopsis vriesii (CANV). Here we review the current state of knowledge about O. ophiodiicola and SFD. In addition, we provide original findings which demonstrate that O. ophiodiicola is widely distributed in eastern North America, has a broad host range, is the predominant cause of fungal skin infections in wild snakes and often causes mild infections in snakes emerging from hibernation. This new information, together with what is already available in the scientific literature, advances our knowledge of the cause, pathogenesis and ecology of SFD. However, additional research is necessary to elucidate the factors driving the emergence of this disease and develop strategies to mitigate its impacts.

Philosophical Transactions of the Royal Society B:↗

USGS2015

Accounting for multiple climate components when estimating climate change exposure and velocity

The effect of anthropogenic climate change on organisms will likely be related to climate change exposure and velocity at local and regional scales. However, common methods to estimate climate change exposure and velocity ignore important components of climate that are known to affect the ecology and evolution of organisms. We develop a novel index of climate change (climate overlap) that simultaneously estimates changes in the means, variation and correlation between multiple weather variables. Specifically, we estimate the overlap between multivariate normal probability distributions representing historical and current or projected future climates. We provide methods for estimating the statistical significance of climate overlap values and methods to estimate velocity using climate overlap. We show that climates have changed significantly across 80% of the continental United States in the last 32 years and that much of this change is due to changes in the variation and correlation between weather variables (two statistics that are rarely incorporated into climate change studies). We also show that projected future temperatures are predicted to be locally novel (<1·5% overlap) across most of the global land surface and that exposure is likely to be highest in areas with low historical climate variation. Last, we show that accounting for changes in the variation and correlation between multiple weather variables can dramatically affect velocity estimates; mean velocity estimates in the continental United States were between 3·1 and 19·0 km yr −1 when estimated using climate overlap compared to 1·4 km yr −1 when estimated using traditional methods. Our results suggest that accounting for changes in the means, variation and correlation between multiple weather variables can dramatically affect estimates of climate change exposure and velocity. These climate components are known to affect the ecology and evolution of organisms, but are ignored by most measures of climate change. We conclude with a set of future directions and recommend future work to determine which measures of climate change exposure and velocity are most related to biological responses to climate change.

Methods in Ecology and Evolution↗

USGS2015

Urgent need for warming experiments in tropical forests

Although tropical forests account for only a fraction of the planet's terrestrial surface, they exchange more carbon dioxide with the atmosphere than any other biome on Earth, and thus play a disproportionate role in the global climate. In the next 20 years, the tropics will experience unprecedented warming, yet there is exceedingly high uncertainty about their potential responses to this imminent climatic change. Here, we prioritize research approaches given both funding and logistical constraints in order to resolve major uncertainties about how tropical forests function and also to improve predictive capacity of earth system models. We investigate overall model uncertainty of tropical latitudes and explore the scientific benefits and inevitable trade-offs inherent in large-scale manipulative field experiments. With a Coupled Model Intercomparison Project Phase 5 analysis, we found that model variability in projected net ecosystem production was nearly 3 times greater in the tropics than for any other latitude. Through a review of the most current literature, we concluded that manipulative warming experiments are vital to accurately predict future tropical forest carbon balance, and we further recommend the establishment of a network of comparable studies spanning gradients of precipitation, edaphic qualities, plant types, and/or land use change. We provide arguments for long-term, single-factor warming experiments that incorporate warming of the most biogeochemically active ecosystem components (i.e. leaves, roots, soil microbes). Hypothesis testing of underlying mechanisms should be a priority, along with improving model parameterization and constraints. No single tropical forest is representative of all tropical forests; therefore logistical feasibility should be the most important consideration for locating large-scale manipulative experiments. Above all, we advocate for multi-faceted research programs, and we offer arguments for what we consider the most powerful and urgent way forward in order to improve our understanding of tropical forest responses to climate change.

Global Change Biology↗

USGS2017

Comparison of four modeling tools for the prediction of potential distribution for non-indigenous weeds in the United States

This study compares four models for predicting the potential distribution of non-indigenous weed species in the conterminous U.S. The comparison focused on evaluating modeling tools and protocols as currently used for weed risk assessment or for predicting the potential distribution of invasive weeds. We used six weed species (three highly invasive and three less invasive non-indigenous species) that have been established in the U.S. for more than 75 years. The experiment involved providing non-U. S. location data to users familiar with one of the four evaluated techniques, who then developed predictive models that were applied to the United States without knowing the identity of the species or its U.S. distribution. We compared a simple GIS climate matching technique known as Proto3, a simple climate matching tool CLIMEX Match Climates, the correlative model MaxEnt, and a process model known as the Thornley Transport Resistance (TTR) model. Two experienced users ran each modeling tool except TTR, which had one user. Models were trained with global species distribution data excluding any U.S. data, and then were evaluated using the current known U.S. distribution. The influence of weed species identity and modeling tool on prevalence and sensitivity effects was compared using a generalized linear mixed model. Each modeling tool itself had a low statistical significance, while weed species alone accounted for 69.1 and 48.5% of the variance for prevalence and sensitivity, respectively. These results suggest that simple modeling tools might perform as well as complex ones in the case of predicting potential distribution for a weed not yet present in the United States. Considerations of model accuracy should also be balanced with those of reproducibility and ease of use. More important than the choice of modeling tool is the construction of robust protocols and testing both new and experienced users under blind test conditions that approximate operational conditions.

Biological Invasions↗

USGS2022

Ecological and socioeconomic factors associated with the human burden of environmentally mediated pathogens: A global analysis

Background Billions of people living in poverty are at risk of environmentally mediated infectious diseases—that is, pathogens with environmental reservoirs that affect disease persistence and control and where environmental control of pathogens can reduce human risk. The complex ecology of these diseases creates a global health problem not easily solved with medical treatment alone. Methods We quantified the current global disease burden caused by environmentally mediated infectious diseases and used a structural equation model to explore environmental and socioeconomic factors associated with the human burden of environmentally mediated pathogens across all countries. Findings We found that around 80% (455 of 560) of WHO-tracked pathogen species known to infect humans are environmentally mediated, causing about 40% (129 488 of 359 341 disability-adjusted life years) of contemporary infectious disease burden (global loss of 130 million years of healthy life annually). The majority of this environmentally mediated disease burden occurs in tropical countries, and the poorest countries carry the highest burdens across all latitudes. We found weak associations between disease burden and biodiversity or agricultural land use at the global scale. In contrast, the proportion of people with rural poor livelihoods in a country was a strong proximate indicator of environmentally mediated infectious disease burden. Political stability and wealth were associated with improved sanitation, better health care, and lower proportions of rural poverty, indirectly resulting in lower burdens of environmentally mediated infections. Rarely, environmentally mediated pathogens can evolve into global pandemics (eg, HIV, COVID-19) affecting even the wealthiest communities. Interpretation The high and uneven burden of environmentally mediated infections highlights the need for innovative social and ecological interventions to complement biomedical advances in the pursuit of global health and sustainability goals. Funding Bill & Melinda Gates Foundation, National Institutes of Health, National Science Foundation, Alfred P. Sloan Foundation, National Institute for Mathematical and Biological Synthesis, Stanford University, and the US Defense Advanced Research Projects Agency.

The Lancet Planetary Health↗

USGS2014

A synthesis of methane emissions from 71 northern, temperate, and subtropical wetlands

Wetlands are the largest natural source of atmospheric methane. Here, we assess controls on methane flux using a database of approximately 19 000 instantaneous measurements from 71 wetland sites located across subtropical, temperate, and northern high latitude regions. Our analyses confirm general controls on wetland methane emissions from soil temperature, water table, and vegetation, but also show that these relationships are modified depending on wetland type (bog, fen, or swamp), region (subarctic to temperate), and disturbance. Fen methane flux was more sensitive to vegetation and less sensitive to temperature than bog or swamp fluxes. The optimal water table for methane flux was consistently below the peat surface in bogs, close to the peat surface in poor fens, and above the peat surface in rich fens. However, the largest flux in bogs occurred when dry 30-day averaged antecedent conditions were followed by wet conditions, while in fens and swamps, the largest flux occurred when both 30-day averaged antecedent and current conditions were wet. Drained wetlands exhibited distinct characteristics, e.g. the absence of large flux following wet and warm conditions, suggesting that the same functional relationships between methane flux and environmental conditions cannot be used across pristine and disturbed wetlands. Together, our results suggest that water table and temperature are dominant controls on methane flux in pristine bogs and swamps, while other processes, such as vascular transport in pristine fens, have the potential to partially override the effect of these controls in other wetland types. Because wetland types vary in methane emissions and have distinct controls, these ecosystems need to be considered separately to yield reliable estimates of global wetland methane release.

Global Change Biology↗

USGS2016

Will changes in phenology track climate change? A study of growth initiation timing in coast Douglas-fir

Under climate change, the reduction of frost risk, onset of warm temperatures and depletion of soil moisture are all likely to occur earlier in the year in many temperate regions. The resilience of tree species will depend on their ability to track these changes in climate with shifts in phenology that lead to earlier growth initiation in the spring. Exposure to warm temperatures (“forcing”) typically triggers growth initiation, but many trees also require exposure to cool temperatures (“chilling”) while dormant to readily initiate growth in the spring. If warming increases forcing and decreases chilling, climate change could maintain, advance or delay growth initiation phenology relative to the onset of favorable conditions. We modeled the timing of height- and diameter-growth initiation in coast Douglas-fir (an ecologically and economically vital tree in western North America) to determine whether changes in phenology are likely to track changes in climate using data from field-based and controlled-environment studies, which included conditions warmer than those currently experienced in the tree's range. For high latitude and elevation portions of the tree's range, our models predicted that warming will lead to earlier growth initiation and allow trees to track changes in the onset of the warm but still moist conditions that favor growth, generally without substantially greater exposure to frost. In contrast, towards lower latitude and elevation range limits, the models predicted that warming will lead to delayed growth initiation relative to changes in climate due to reduced chilling, with trees failing to capture favorable conditions in the earlier parts of the spring. This maladaptive response to climate change was more prevalent for diameter-growth initiation than height-growth initiation. The decoupling of growth initiation with the onset of favorable climatic conditions could reduce the resilience of coast Douglas-fir to climate change at the warm edges of its distribution.

California, Oregon, Washington↗

USGS1999

Status and distribution of the angonoka tortoise ( Geochelone yniphora ) of western Madagascar

From 1993 to 1995, field surveys were conducted in western Madagascar to assess the current status of the angonoka tortoise ( Geochelone yniphora ) in the wild. Tortoise presence was documented at 10 of 11 localities surveyed. These localities represent at least five populations, all within a 30-km radius of Baly Bay, near the town of Soalala. The populations occur on fragments of habitat ranging from <50 to 4–6000 ha in size. One hundred and forty-five tortoises were marked in the five populations. Hatchling or juvenile tortoises were observed in all populations, indicating that reproduction was occurring. Most of the 145 tortoises (68%) were marked on Cape Sada, where monthly surveys were conducted. The tortoise density on the c. 150 ha peninsula was 0.66 tortoises/ha. The remains of 22 dead juveniles were found on Cape Sada over the 2-year period. This evidence, combined with the low number of juveniles in intermediate size classes in the Cape Sada population suggests that juvenile mortality may be high.

Biological Conservation↗

USGS2020

Altered climate leads to positive density‐dependent feedbacks in a tropical wet forest

Climate change is predicted to result in warmer and drier Neotropical forests relative to current conditions. Negative density‐dependent feedbacks, mediated by natural enemies, are key to maintaining the high diversity of tree species found in the tropics, yet we have little understanding of how projected changes in climate are likely to affect these critical controls. Over 3 years, we evaluated the effects of a natural drought and in situ experimental warming on density‐dependent feedbacks on seedling demography in a wet tropical forest in Puerto Rico. In the +4°C warming treatment, we found that seedling survival increased with increasing density of the same species (conspecific). These positive density‐dependent feedbacks were not associated with a decrease in aboveground natural enemy pressure. If positive density‐dependent feedbacks are not transient, the diversity of tropical wet forests, which may rely on negative density dependence to drive diversity, could decline in a future warmer, drier world.

Puerto Rico↗

USGS2014

Recent population size, trends, and limiting factors for the double-crested Cormorant in Western North America

The status of the double-crested cormorant ( Phalacrocorax auritus ) in western North America was last evaluated during 1987–2003. In the interim, concern has grown over the potential impact of predation by double-crested cormorants on juvenile salmonids ( Oncorhynchus spp.), particularly in the Columbia Basin and along the Pacific coast where some salmonids are listed for protection under the United States Endangered Species Act. Recent re-evaluations of double-crested cormorant management at the local, flyway, and federal level warrant further examination of the current population size and trends in western North America. We collected colony size data for the western population (British Columbia, Washington, Oregon, Idaho, California, Nevada, Utah, Arizona, and the portions of Montana, Wyoming, Colorado and New Mexico west of the Continental Divide) by conducting aircraft-, boat-, or ground-based surveys and by cooperating with government agencies, universities, and non-profit organizations. In 2009, we estimated approximately 31,200 breeding pairs in the western population. We estimated that cormorant numbers in the Pacific Region (British Columbia, Washington, Oregon, and California) increased 72% from 1987–1992 to circa 2009. Based on the best available data for this period, the average annual growth rate (λ) of the number of breeding birds in the Pacific Region was 1.03, versus 1.07 for the population east of the Continental Divide during recent decades. Most of the increase in the Pacific Region can be attributed to an increase in the size of the nesting colony on East Sand Island in the Columbia River estuary, which accounts for about 39% of all breeding pairs in the western population and is the largest known breeding colony for the species (12,087 breeding pairs estimated in 2009). In contrast, numbers of breeding pairs estimated in coastal British Columbia and Washington have declined by approximately 66% during this same period. Disturbance at breeding colonies by bald eagles ( Haliaeetus leucocephalus ) and humans are likely limiting factors on the growth of the western population at present. Because of differences in biology and management, the western population of double-crested cormorants warrants consideration as a separate management unit from the population east of the Continental Divide.

Journal of Wildlife Management↗

USGS2016

Estimating indices of range shifts in birds using dynamic models when detection is imperfect

There is intense interest in basic and applied ecology about the effect of global change on current and future species distributions. Projections based on widely used static modeling methods implicitly assume that species are in equilibrium with the environment and that detection during surveys is perfect. We used multiseason correlated detection occupancy models, which avoid these assumptions, to relate climate data to distributional shifts of Louisiana Waterthrush in the North American Breeding Bird Survey (BBS) data. We summarized these shifts with indices of range size and position and compared them to the same indices obtained using more basic modeling approaches. Detection rates during point counts in BBS surveys were low, and models that ignored imperfect detection severely underestimated the proportion of area occupied and slightly overestimated mean latitude. Static models indicated Louisiana Waterthrush distribution was most closely associated with moderate temperatures, while dynamic occupancy models indicated that initial occupancy was associated with diurnal temperature ranges and colonization of sites was associated with moderate precipitation. Overall, the proportion of area occupied and mean latitude changed little during the 1997–2013 study period. Near-term forecasts of species distribution generated by dynamic models were more similar to subsequently observed distributions than forecasts from static models. Occupancy models incorporating a finite mixture model on detection – a new extension to correlated detection occupancy models – were better supported and may reduce bias associated with detection heterogeneity. We argue that replacing phenomenological static models with more mechanistic dynamic models can improve projections of future species distributions. In turn, better projections can improve biodiversity forecasts, management decisions, and understanding of global change biology.

Global Change Biology↗

USGS2021

Testing a generalizable machine learning workflow for aquatic invasive species on Rainbow Trout (Oncorhynchus mykiss) in northwest Montana

Biological invasions are accelerating worldwide, causing major ecological and economic impacts in aquatic ecosystems. The urgent decision-making needs of invasive species managers can be better met by the integration of biodiversity big data with large-domain models and data-driven products. Remotely sensed data products can be combined with existing invasive species occurrence data via machine learning models to provide the proactive spatial risk analysis necessary for implementing coordinated and agile management paradigms across large scales. We present a workflow that generates rapid spatial risk assessments on aquatic invasive species using occurrence data, spatially explicit environmental data, and an ensemble approach to species distribution modeling using five machine learning algorithms. For proof of concept and validation, we tested this workflow using extensive spatial and temporal hybridization and occurrence data from a well-studied, ongoing, and climate-driven species invasion in the upper Flathead River system in northwestern Montana, USA. Rainbow Trout (RBT; Oncorhynchus mykiss), an introduced species in the Flathead River basin, compete and readily hybridize with native Westslope Cutthroat Trout (WCT; O. clarkii lewisii), and the spread of RBT individuals and their alleles has been tracked for decades. We used remotely sensed and other geospatial data as key environmental predictors for projecting resultant habitat suitability to geographic space. The ensemble modeling technique yielded high accuracy predictions relative to 30-fold cross-validated datasets (87% 30-fold cross-validated accuracy score). Both top predictors and model performance relative to these predictors matched current understanding of the drivers of RBT invasion and habitat suitability, indicating that temperature is a major factor influencing the spread of invasive RBT and hybridization with native WCT. The congruence between more time-consuming modeling approaches and our rapid machine-learning approach suggest that this workflow could be applied more broadly to provide data-driven management information for early detection of potential invaders.

Alberta, British Columbia, Montana↗

USGS2010

Antibiotic use during the intracoelomic implantation of electronic tags into fish

The use of antibiotics, in particular, the use of a single dose of antibiotics during electronic tag implantation is of unproven value, and carries with it the potential for the development of antibiotic resistance in bacteria and the alteration of the immune response of the fish. Antibiotic use during electronic tag implantation must conform to relevant drug laws and regulations in the country where work is being done, including the requirements for withdrawal times before human consumption is a possibility. Currently, the choice of antibiotics (most often tetracycline or oxytetracycline) and the use of a single dose of the drug are decisions made without knowledge of the basic need for antibiotic usage and of the bacteria involved in infections that occur following electronic tag implantation. Correct perioperative use of an antibiotic is to apply the drug to the animal before surgery begins, to assure serum and tissue levels of the drug are adequate before the incision is made. However, the most common perioperative application of antibiotics during implantation of an electronic tag is to delay the administration of the drug, injecting it into the coelom after the electronic tag is inserted, just prior to closure of the incision. There is little empirical evidence that the present application of antibiotics in fish being implanted with electronic tags is of value. Improvements should first be made to surgical techniques, especially the use of aseptic techniques and sterilized instruments and electronic tags, before resorting to antibiotics.

Reviews in Fish Biology and Fisheries↗

USGS2022

Continuous water-quality and suspended-sediment transport monitoring in San Francisco Bay, California, water years 2020–21

The U.S. Geological Survey (USGS) has continuously monitored real-time water quality and suspended-sediment transport in San Francisco Bay (the Bay) since 1989 as part of a multi-agency effort (see “Acknowledgments” section) to address estuary management, water supply, and ecological concerns. The San Francisco Bay area is home to millions of people and biologically diverse marine and terrestrial flora and fauna. Freshwater mixes with saltwater in the Bay and is subject to riverine influences (floods, droughts, managed reservoir releases, and freshwater diversions) and marine influences (tides, waves, and effects of saltwater). Water temperature, salinity, suspended-sediment concentration (SSC), and turbidity, are used by State and Federal resources managers and are monitored at eight key locations throughout the Bay (fig. 1). Water temperature and salinity affect the density of water, which controls gravity-driven circulation patterns and stratification in the water column. Salinity indicates the relative mixing of fresh and ocean waters in the Bay and is derived from specific conductance measurements. Turbidity is a measure of light scattered from suspended particles in the water that is used to estimate suspended-sediment concentration. Suspended-sediment concentrations also are directly measured through depth-integrated water sampling. Suspended sediment affects Bay water quality in multiple ways. Suspended sediment affects phytoplankton growth by attenuating sunlight in the water column. Suspended sediment deposition on tidal marshes and intertidal mudflats helps to restore and sustain these habitats as sea level rises. Settling of suspended sediment in ports and shipping channels creates the need for more dredging. In addition, suspended sediment often carries adsorbed contaminants as it is transported in the water column, which affects the distributions and concentrations of adsorbed contaminants in the environment. Excessive concentrations of sediment-adsorbed contaminants in deposits on the bottom of the Bay can affect ecosystem health. External factors, such as tidal currents, waves, and wind can also affect water quality in the Bay. Tidal currents in the Bay change direction four times daily, and wind direction and intensity typically fluctuate on a daily cycle. Consequently, salinity, water temperature, and suspended-sediment concentration differ spatially and temporally throughout the Bay. Therefore, high-frequency measurements at multiple locations are needed to monitor these changes. Data collected at eight stations throughout the Bay are transmitted in near real-time using cellular telemetry and posted to the USGS National Water Information System (NWIS; https://waterdata.usgs.gov/usa/nwis ). The purposes of this fact sheet are to (1) provide information about the USGS San Francisco Bay water-quality monitoring network; (2) highlight various applications in which these data can be used; and (3) provide internet links to access the resulting continuous water-quality data collected by the USGS.

California↗

USGS2011

A decision-analytic approach to the optimal allocation of resources for endangered species consultation

The resources available to support conservation work, whether time or money, are limited. Decision makers need methods to help them identify the optimal allocation of limited resources to meet conservation goals, and decision analysis is uniquely suited to assist with the development of such methods. In recent years, a number of case studies have been described that examine optimal conservation decisions under fiscal constraints; here we develop methods to look at other types of constraints, including limited staff and regulatory deadlines. In the US, Section Seven consultation, an important component of protection under the federal Endangered Species Act, requires that federal agencies overseeing projects consult with federal biologists to avoid jeopardizing species. A benefit of consultation is negotiation of project modifications that lessen impacts on species, so staff time allocated to consultation supports conservation. However, some offices have experienced declining staff, potentially reducing the efficacy of consultation. This is true of the US Fish and Wildlife Service's Washington Fish and Wildlife Office (WFWO) and its consultation work on federally-threatened bull trout (Salvelinus confluentus). To improve effectiveness, WFWO managers needed a tool to help allocate this work to maximize conservation benefits. We used a decision-analytic approach to score projects based on the value of staff time investment, and then identified an optimal decision rule for how scored projects would be allocated across bins, where projects in different bins received different time investments. We found that, given current staff, the optimal decision rule placed 80% of informal consultations (those where expected effects are beneficial, insignificant, or discountable) in a short bin where they would be completed without negotiating changes. The remaining 20% would be placed in a long bin, warranting an investment of seven days, including time for negotiation. For formal consultations (those where expected effects are significant), 82% of projects would be placed in a long bin, with an average time investment of 15. days. The WFWO is using this decision-support tool to help allocate staff time. Because workload allocation decisions are iterative, we describe a monitoring plan designed to increase the tool's efficacy over time. This work has general application beyond Section Seven consultation, in that it provides a framework for efficient investment of staff time in conservation when such time is limited and when regulatory deadlines prevent an unconstrained approach. ?? 2010.

Biological Conservation↗

USGS2021

A framework for allocating conservation resources among multiple threats and actions

Land managers decide how to allocate resources among multiple threats that can be addressed through multiple possible actions. Additionally, these actions vary in feasibility, effectiveness, and cost. We sought to provide a way to optimize resource allocation to address multiple threats when multiple management options are available, including mutually exclusive options. Formulating the decision as a combinatorial optimization problem, our framework takes as inputs the expected impact and cost of each threat for each action (including do nothing) and for each overall budget identifies the optimal action to take for each threat. We compared the optimal solution to an easy to calculate greedy algorithm approximation and a variety of plausible ranking schemes. We applied the framework to management of multiple introduced plant species in Australian alpine areas. We developed a model of invasion to predict the expected impact in 50 years for each species‐action combination that accounted for each species’ current invasion state (absent, localized, widespread); arrival probability; spread rate; impact, if present, of each species; and management effectiveness of each species‐action combination. We found that the recommended action for a threat changed with budget; there was no single optimal management action for each species; and considering more than one candidate action can substantially increase the management plan's overall efficiency. The approximate solution (solution ranked by marginal cost‐effectiveness) performed well when the budget matched the cost of the prioritized actions, indicating that this approach would be effective if the budget was set as part of the prioritization process. The ranking schemes varied in performance, and achieving a close to optimal solution was not guaranteed. Global sensitivity analysis revealed a threat's expected impact and, to a lesser extent, management effectiveness were the most influential parameters, emphasizing the need to focus research and monitoring efforts on their quantification.

Conservation Biology↗