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Teaching citizen science skills online: Implications for invasive species training programs

Citizen science programs are emerging as an efficient way to increase data collection and help monitor invasive species. Effective invasive species monitoring requires rigid data quality assurances if expensive control efforts are to be guided by volunteer data. To achieve data quality, effective online training is needed to improve field skills and reach large numbers of remote sentinel volunteers critical to early detection and rapid response. The authors evaluated the effectiveness of online static and multimedia tutorials to teach citizen science volunteers (n = 54) how to identify invasive plants; establish monitoring plots; measure percent cover; and use Global Positioning System (GPS) units. Participants trained using static and multimedia tutorials provided less (p <.001) correct species identifications (63% and 67%) than did professionals (83%) across all species, but they did not differ (p =.125) between each other. However, their ability to identify conspicuous species was comparable to that of professionals. The variability in percent plant cover estimates between static (??10%) and multimedia (??13%) participants did not differ (p =.86 and.08, respectively) from those of professionals (??9%). Trained volunteers struggled with plot setup and GPS skills. Overall, the online approach used did not influence conferred field skills and abilities. Traditional or multimedia online training augmented with more rigorous, repeated, and hands-on, in-person training in specialized skills required for more difficult tasks will likely improve volunteer abilities, data quality, and overall program effectiveness. ?? Taylor & Francis Group, LLC.

Applied Environmental Education and Communication↗

H-binding of size- and polarity-fractionated soil and lignite humic acids after removal of metal and ash components

A fractionation technique, combining dialysis removal of metal and ash components with hydrofluoric acid and pH 10 citrate buffer followed by chromatography of dialysis permeate on XAD-8 resin at decreasing pH values, has been applied to lignite humic acid (lignite-HA) and soil humic acid (soil-HA). H-binding data and non ideal competitive adsorption-Donnan model parameters were obtained for the HA fractions by theoretical analysis of H-binding data which reveal a significant increase of the carboxyl and the phenolic charge for the lignite-HA fractions vs. the parental lignite humic acid (L Parental HA). The fractionated lignite-HA material consisted mainly of permeate fractions, some of which were fulvic acid-like. The fractionated soil-HA material consisted mainly of large macromolecular structures that did not permeate the dialysis membrane during deashing. Chargeable groups had comparable concentrations in soil-HA fractions and parental soil humic acid (S Parental HA), indicating minimal interference of ash components with carboxyl and phenolic (and/or enolic) groups. Fractionation of HA, combined with theoretical analysis of H-binding, can distinguish the supramolecular vs. macromolecular nature of fractions within the same parental HA.

Environmental Science and Pollution Research↗

Vulnerability of mangrove resources to sea-level rise on Sanibel Island, Florida, USA

Accelerating sea-level rise (SLR) is poised to reshape coastal environments over the coming decades, providing a challenge to land managers who need actionable information. Mangroves have an innate ability to keep pace with some SLR but may drown under the higher rates projected by the end of the century. Understanding local mangrove resilience to SLR requires understanding of historic and contemporary accretion rates, productivity, and forest elevations relative to tidal inundation. We applied the WARMER3 modeling framework to assess future mangrove resilience to SLR and blue carbon storage across the “Ding” Darling National Wildlife Refuge on Sanibel Island in southwest Florida, USA. We found that Sanibel mangroves are sensitive to the SLR scenario, with projected losses ranging from 19 to 70% by 2100. Across SLR scenarios, projected areal extent was similar until about 2035 and then diverge, coincident with projected acceleration in the rate of SLR. Threshold analysis indicates found that Sanibel mangroves are likely to submerge when rates exceed 6.5 mm yr −1 . Currently, the mangrove forest of our study domain holds an estimated 214,000 Mg of carbon but is likely to decrease as mangroves convert to open water in the second half of this century. For “Ding” Darling, these site-specific projections identify when losses in mangrove resources are most likely, providing a basis to prioritize local management actions and conservation resources.

Florida↗

Loess sedimentation in Tibet: provenance, processes, and link with Quaternary glaciations

Well-preserved loess deposits are found on the foothills of mountains along the middle reaches of the Yarlung Zangbo River in southern Tibet. Optically stimulated luminescence (OSL) dating is used to determine loess ages by applying the single-aliquot regeneration technique. Geochemical, mineralogical, and granulometric measurements were carried out to allow a comparison between loess from Tibet and the Chinese Loess Plateau. Our results demonstrate that (i) the loess deposits have a basal age of 13-11 ka, suggesting they accumulated after the last deglaciation, (ii) loess in southern Tibet has a "glacial" origin, resulting from eolian sorting of glaciofluvial outwash deposits from braided river channels or alluvial fans by local near-surface winds, and (iii) the present loess in the interior of Tibet has accumulated since the last deglaciation when increased monsoonal circulation provided an increased vegetation cover that was sufficient for trapping eolian silt. The lack of full-glacial loess is either due to minimal vegetation cover or possibly due to the erosion of loess as glaciofluvial outwash during the beginning of each interglacial. Such processes would have been repeated during each glacial-interglacial cycle of the Quaternary. ?? 2007 Elsevier Ltd. All rights reserved.

Quaternary Science Reviews↗

Wastewater-based epidemiology pilot study to examine drug use in the Western United States

The extent of prescription and illicit drug abuse in geographically isolated rural and micropolitan communities in the intermountain western United States (US) has not been well tracked. The goal of this pilot study was to accurately measure drug dose consumption rates (DCR) between two select populations, normalize the data and compare the DCRs to similar communities. To learn about patterns of drug abuse between the two disparate communities, we used the emergent field of wastewater-based epidemiology (WBE). A rapid, quantitative and systematic process for the determination of multiple classes of prescribed and illicit drugs was applied to influent wastewater samples. Influent samples were collected over the course of three months (April to June 2019) at two wastewater treatment plants representing a small urban and a rural community. Collection of sewage influent included 24-h composite samples and the use of polar organic chemical integrative samplers (POCIS), time-weighted samplers. Using the results from the composite sampling data, DCRs per 1000 population could be calculated from the concentration data and the use of excretion correction factors. The following 18 compounds: amphetamine, methamphetamine, MDA, MDMA, morphine, 6-acetylmorphine, methadone, EDDP, codeine, benzoylecgonine, hydrocodone, hydromorphone, oxycodone, noroxycodone, ketamine, fluoxetine, tramadol, and ritalinic acid; represent a subset of the targeted analytes that were consistently measured at detectable concentration levels, and present at both sites. Following normalization of the drug measurements to influent flow rates and per capita, the small urban community demonstrated greater collective excretion rates (CER) than the rural community, with the exceptions of amphetamine and methamphetamine.

Science of the Total Environment↗

High frequency data exposes nonlinear seasonal controls on dissolved organic matter in a large watershed

We analyzed a five year, high frequency time series generated by an in situ fluorescent dissolved organic matter (fDOM) sensor installed near the Connecticut River’s mouth, investigating high temporal resolution DOM dynamics in a larger watershed and longer time series than previously addressed. We identified a gradient between large, saturating summer fDOM responses to discharge and linear, subdued responses during colder months. Seasonal response patterns were not consistent with multiple linear regression. Alternatively, we binned measurements across the yearly cycle using environmental indices, such as temperature, and applied moving regression, a novel approach which produced superior fits to calendar day binning. Spatially averaged watershed soil temperature at 10 cm was the best overall index of discharge-fDOM response. DOM fractionation showed fDOM was primarily a surrogate for hydrophobic organic acid (HPOA) concentrations. HPOAs were highly correlated with discharge, but hydrophilics (HPIs) were not. Discharge dependent DOM concentrations driven by the HPOA fraction may be controlled by soil temperature and water table position relative to organic and mineral soil horizons. HPI concentrations were correlated with average watershed soil temperature at 10 cm but were rather stationary throughout the year, further indicating a consistent groundwater source for this nonfluorescent DOM. We present a resolved subseasonal empirical model of DOM concentrations and fluxes, showing that riverine DOM flux and quality depend heavily on seasonal terrestrial carbon dynamics and hydrologic flow paths. High frequency monitoring reveals readily discernible patterns demonstrating that upland biogeochemical signals are maintained even at this large watershed scale.

Environmental Science and Technology↗

Real-time nowcasting of microbiological water quality at recreational beaches: A wavelet and artificial neural network-based hybrid modeling approach

The number of beach closings caused by bacterial contamination has continued to rise in recent years, putting beachgoers at risk of exposure to contaminated water. Current approaches predict levels of indicator bacteria using regression models containing a number of explanatory variables. Data-based modeling approaches can supplement routine monitoring data and provide highly accurate short-term forecasts of beach water quality. In this paper, we apply the nonlinear autoregressive network with exogenous inputs (NARX) method with explanatory variables to predict Escherichia coli concentrations at four Lake Michigan beach sites. We also apply the nonlinear input–output network (NIO) and nonlinear autoregressive neural network (NAR) methods in addition to a hybrid wavelet-NAR (WA-NAR) model and demonstrate their application. All models were tested using 3 months of observed data. Results revealed that the NARX models provided the best performance and that the WA-NAR model, which requires no explanatory variables, outperformed the NIO and NAR models; therefore, the WA-NAR model is suitable for application to data scarce regions. The models proposed in this paper were evaluated using multiple performance metrics, including sensitivity and specificity measures, and produced results comparable or superior to those of previous mechanistic and statistical models developed for the same beach sites. The relatively high R 2 values between data and the NARX models ( R 2 values of ∼0.8 for the beach sites and ∼0.9 for the river site) indicate that the new class of models shows promise for beach management.

Environmental Science & Technology↗

Mars sample return campaign: Biological risk and a proposed sample safety assessment protocol

Returning surface samples from Mars to Earth has been a major planetary science objective, with the potential for the detection of microbiological life and the possibility of improving our understanding of the origins of life. The National Aeronautics and Space Administration and the European Space Agency assembled a team to assess the level of risk that returned samples could contain potential biohazards. The team was chartered with optimizing previous sample safety assessment strategies, defining what constitutes a biological hazard, developing a protocol to test for biohazards, and establishing a statistical framework to determine if samples may be safe for release from a high-containment facility. This report presents the biological context for a proposed three-step protocol for testing returned samples, including how to determine if microorganisms are present, and if they could be (or were recently) alive.

Applied and Environmental Microbiology↗

Acidification in the U.S. Southeast: Causes, potential consequences and the role of the Southeast Ocean and Coastal Acidification Network

Coastal acidification in southeastern U.S. estuaries and coastal waters is influenced by biological activity, run-off from the land, and increasing carbon dioxide in the atmosphere. Acidification can negatively impact coastal resources such as shellfish, finfish, and coral reefs, and the communities that rely on them. Organismal responses for species located in the U.S. Southeast document large negative impacts of acidification, especially in larval stages. For example, the toxicity of pesticides increases under acidified conditions and the combination of acidification and low oxygen has profoundly negative influences on genes regulating oxygen consumption. In corals, the rate of calcification decreases with acidification and processes such as wound recovery, reproduction, and recruitment are negatively impacted. Minimizing the changes in global ocean chemistry will ultimately depend on the reduction of carbon dioxide emissions, but adaptation to these changes and mitigation of the local stressors that exacerbate global acidification can be addressed locally. The evolution of our knowledge of acidification, from basic understanding of the problem to the emergence of applied research and monitoring, has been facilitated by the development of regional Coastal Acidification Networks (CANs) across the United States. This synthesis is a product of the Southeast Coastal and Ocean Acidification Network (SOCAN). SOCAN was established to better understand acidification in the coastal waters of the U.S. Southeast and to foster communication among scientists, resource managers, businesses, and governments in the region. Here we review acidification issues in the U.S. Southeast, including the regional mechanisms of acidification and their potential impacts on biological resources and coastal communities. We recommend research and monitoring priorities and discuss the role SOCAN has in advancing acidification research and mitigation of and adaptation to these changes.

Florida, Georgia, North Carolina, South Carolina↗

Soil amendment effects on the exotic annual grass Bromus tectorum L. and facilitation of its growth by the native perennial grass Hilaria jamesii (Torr.) Benth

Greenhouse experiments were undertaken to identify soil factors that curtail growth of the exotic annual grass Bromus tectorum L. (cheatgrass) without significantly inhibiting growth of native perennial grasses (here represented by Hilaria jamesii [Torr.] Benth). We grew B. tectorum and H. jamesii alone (monoculture pots) and together (combination pots) in soil treatments that manipulated levels of soil phosphorus, potassium, and sodium. Hilaria jamesii showed no decline when its aboveground biomass in any of the applied treatments was compared to the control in either the monoculture or combination pots. Monoculture pots of B. tectorum showed a decline in aboveground biomass with the addition of Na 2 HPO 4 and K 2 HPO 4. Interestingly, in pots where H. jamesii was present, the negative effect of these treatments was ameliorated. Whereas the presence of B. tectorum generally decreased the aboveground biomass of H. jamesii (comparing aboveground biomass in monoculture versus combination pots), the presence of H. jamesii resulted in an enhancement of B. tectorum aboveground biomass by up to 900%. We hypothesize that B. tectorum was able to obtain resources from H. jamesii, an action that benefited B. tectorum while generally harming H. jamesii. Possible ways resources may be gained by B. tectorum from native perennial grasses include (1) B. tectorum is protected from salt stress by native plants or associated soil biota; (2) when B. tectorum is grown with H. jamesii, the native soil biota is altered in a way that favors B. tectorum growth, including B. tectorum tapping into the mycorrhizal network of native plants and obtaining resources from them; (3) B. tectorum can take advantage of root exudates from native plants, including water and nutrients released by natives via hydraulic redistribution; and (4) B. tectorum is able to utilize some combination of the above mechanisms. In summary, land managers may find adding soil treatments can temporarily suppress B. tectorum and enhance the establishment of native plants. However, the extirpation of B. tectorum is unlikely, as many native grasses are likely to facilitate its growth. ?? 2008 Springer Science+Business Media B.V.

Plant Ecology↗

Promoting synergy in the innovative use of environmental data—Workshop summary

From December 2 to 4, 2015, NatureServe and the U.S. Geological Survey organized and hosted a biodiversity and ecological informatics workshop at the U.S. Department of the Interior in Washington, D.C. The workshop objective was to identify user-driven future directions and areas of collaboration in advanced applications of environmental data applied to forecasting and decision making for the sustainability of biodiversity and ecosystem services. Substantial effort to recruit attendees from diverse Federal, State, and private sector organizations successfully attracted participants from 20 Federal agencies and 48 different institutions in the academic, nonprofit, State government, and commercial sectors; the total number of attendees ranged from 100 to 144 during the 3-day workshop. The first one-half of the workshop was divided into 7 plenary sessions and 3 sets of lightning talk sessions organized by sector, providing 48 oral and visual plenary presentations that shared diverse perspectives on biodiversity and ecological informatics, including original biospatial analyses from 6 graduate student map contest winners. The second one-half of the workshop focused on 10 breakout sessions with participant-driven themes from the environmental data sphere and concluded with an address by the Director of the U.S. Fish and Wildlife Service. The workshop was structured to encourage interactivity. About 80–90 percent of attendees provided direct feedback using clicker devices for specific questions related to biodiversity and ecological data uses and needs, and 10 breakout session leaders shared the highlights of their group discussions during the final workshop plenary sessions. Participants were encouraged to use the Twitter hashtag #ShareUrData. Over lunch on day 2 there were 20 simultaneous presentations of tools and apps during a special “Tools Café” session. The 10 participant-defined breakout session topics are listed below: Ecosystem services and ecological indicators Inventory and monitoring Biogeographic map of the Nation Pollinators Invasive species Remote sensing Drivers of agricultural change Citizen science Climate Hydrology and watersheds Numerous common themes that emerged from the workshop include the following: The vital importance of completing foundational environmental datasets that are nationally consistent and are essential to multiple sectors, such as the Soil Survey Geographic database high-resolution soils data, a minimum 5-meter resolution digital elevation model, national hydrographic data, high-resolution land cover data, time series high-resolution spatial climate data from historical to future time steps, and a national wetland inventory. Improved, nationally consistent environmental datasets (integrated with targeted observations) will dramatically advance forecasting capacity and support early warning systems (that is, drought, forest disease); however, multiagency coordination should focus on decision support tools that convey appropriate actions and responses to adapt to, and mitigate, potential negative consequences. Digitizing and providing access to the vast stores of underused historical data that can be leveraged for this purpose is of national importance. Modern computational techniques and the ever-increasing flow of environmental data from ground and remote observations can support improved understanding of environmental change. Success of understanding patterns of change for decision making requires establishing baselines from which change can be measured. The value of digitized historical data is greater than ever before. There is a need to recognize the multifaceted potential of citizen science to engage the public in resource stewardship, to create the next generation of science, technology, engineering, math, and environmental leaders, and to have sufficient field personnel to monitor environmental trends, including early detection of alien invasive species, phenological shifts, shifting distribution and abundance of indicator species, and species inventories. The Federal government has an essential role in creating the infrastructure to dramatically improve mobilization of citizen science (and other) data by fostering the following: creation of data standards, creation of nationally consistent framework datasets, vertical integration of observation data, visualization and dissemination of aggregated datasets, and calculation and communication of derived trends. Current and near future trends in the availability of remotely sensed data (rapid expansion of satellite fleets and drones) is revolutionizing access to near-real-time ecological data. Targeted integration with ground-based observations and instrumentation has an extremely valuable role in validating remotely sensed data, filling data gaps, improving data quality, and fully realizing the potential of the near-real-time monitoring of environmental indicator trends. Integrated management of environmental data at the landscape scale is required even as specific actions on the ground are largely local in nature. The workshop highlighted numerous success stories; however, almost every breakout group pointed out the still-too-fragmented nature of the current data landscape. Management and delivery of the necessary data, tools, and analyses to sustain our Nation’s environmental capital must be a collaborative effort between Federal, State, and local governments, academia, nonprofits, and the commercial sector, even though the responsibilities of each sector are different.

Open-File Report↗

Tracing the uptake of Hg(II) in an iron-reducing bacterium using mercury stable isotopes

Anaerobic microorganisms play a key role in the biological mercury (Hg) cycle due to their ability to produce bioaccumulative neurotoxic methylmercury (MeHg). However, despite recent advances, how bacteria accumulate inorganic Hg [Hg(II)] prior to methylation is largely unknown. In this study, we applied Hg stable isotopes to measure changes in cellular compartments of Geobacter sulfurreducens and a nonmethylating mutant strain to investigate intracellular transport of Hg(II). Both strains accumulated intracellular Hg(II) that was lower in δ 202 Hg relative to dissolved extracellular Hg(II), demonstrating mass-dependent fractionation during uptake. Hg reduction by the mutant strain (50% Hg concentration loss in 24 h) resulted in higher δ 202 Hg values of cellular Hg than in wild-type cells. Further observations showed increasing δ 202 Hg values in dissolved extracellular MeHg and Hg(II) but decreasing δ 202 Hg values of intracellular Hg(II) in wild-type G. sulfurreducens suggesting that external Hg pools may be the proximate source of Hg for methylation in this bacterium. This investigation demonstrates that cellular uptake is comprised of multiple processes and transformations that influence Hg(II) prior to methylation, which can impart distinct isotopic signatures to Hg(II) and MeHg pools in the environment.

Environmental Science and Technology Letters↗

Beach monitoring criteria: reading the fine print

Beach monitoring programs aim to decrease swimming-related illnesses resulting from exposure to harmful microbes in recreational waters, while providing maximum beach access. Managers are advised by the U.S. EPA to estimate microbiological water quality based on a 5-day geometric mean of fecal indicator bacteria (FIB) concentrations or on a jurisdiction-specific single-sample maximum; however, most opt instead to apply a default single-sample maximum to ease application. We examined whether re-evaluation of the U.S. EPA ambient water quality criteria (AWQC) and the epidemiological studies on which they are based could increase public beach access without affecting presumed health risk. Single-sample maxima were calculated using historic monitoring data for 50 beaches along coastal Lake Michigan on various temporal and spatial groupings to assess flexibility in the application of the AWQC. No calculation on either scale was as low as the default maximum (235 CFU/100 mL) that managers typically use, indicating that current applications may be more conservative than the outlined AWQC. It was notable that beaches subject to point source FIB contamination had lower variation, highlighting the bias in the standards for these beaches. Until new water quality standards are promulgated, more site-specific application of the AWQC may benefit beach managers by allowing swimmers greater access to beaches. This issue will be an important consideration in addressing the forthcoming beach monitoring standards.

Environmental Science & Technology↗

HydroBench: Jupyter supported reproducible hydrological model benchmarking and diagnostic tool

Evaluating whether hydrological models are right for the right reasons demands reproducible model benchmarking and diagnostics that evaluate not just statistical predictive model performance but also internal processes. Such model benchmarking and diagnostic efforts will benefit from standardized methods and ready-to-use toolkits. Using the Jupyter platform, this work presents HydroBench, a model-agnostic benchmarking tool consisting of three sets of metrics: 1) common statistical predictive measures, 2) hydrological signature-based process metrics, including a new time-linked flow duration curve and 3) information-theoretic diagnostics that measure the flow of information among model variables. As a test case, HydroBench was applied to compare two model products (calibrated and uncalibrated) of the National Hydrologic Model - Precipitation Runoff Modeling System (NHM-PRMS) at the Cedar River watershed, WA, United States. Although the uncalibrated model has the highest predictive performance, particularly for high flows, the signature-based diagnostics showed that the model overestimates low flows and poorly represents the recession processes. Elucidating why low flows may have been overestimated, the information-theoretic diagnostics indicated a higher flow of information from precipitation to snowmelt to streamflow in the uncalibrated model compared to the calibrated model, where information flowed more directly from precipitation to streamflow. This test case demonstrated the capability of HydroBench in process diagnostics and model predictive and functional performance evaluations, along with their tradeoffs. Having such a model benchmarking tool not only provides modelers with a comprehensive model evaluation system but also provides an open-source tool that can further be developed by the hydrological community.

Frontiers in Earth Sciences↗

Potential for calibration of geostationary meteorological satellite imagers using the Moon

Solar-band imagery from geostationary meteorological satellites has been utilized in a number of important applications in Earth Science that require radiometric calibration. Because these satellite systems typically lack on-board calibrators, various techniques have been employed to establish "ground truth", including observations of stable ground sites and oceans, and cross-calibrating with coincident observations made by instruments with on-board calibration systems. The Moon appears regularly in the margins and corners of full-disk operational images of the Earth acquired by meteorological instruments with a rectangular field of regard, typically several times each month, which provides an excellent opportunity for radiometric calibration. The USGS RObotic Lunar Observatory (ROLO) project has developed the capability for on-orbit calibration using the Moon via a model for lunar spectral irradiance that accommodates the geometries of illumination and viewing by a spacecraft. The ROLO model has been used to determine on-orbit response characteristics for several NASA EOS instruments in low Earth orbit. Relative response trending with precision approaching 0.1% per year has been achieved for SeaWiFS as a result of the long time-series of lunar observations collected by that instrument. The method has a demonstrated capability for cross-calibration of different instruments that have viewed the Moon. The Moon appears skewed in high-resolution meteorological images, primarily due to satellite orbital motion during acquisition; however, the geometric correction for this is straightforward. By integrating the lunar disk image to an equivalent irradiance, and using knowledge of the sensor's spectral response, a calibration can be developed through comparison against the ROLO lunar model. The inherent stability of the lunar surface means that lunar calibration can be applied to observations made at any time, including retroactively. Archived geostationary imager data that contains the Moon can be used to develop response histories for these instruments, regardless of their current operational status.

Conference Paper↗

Decision context as an essential component of population viability analysis

Population viability analysis (PVA) is a widely used tool that applies demographic data in simulation frameworks to assess extinction risk for species or populations. It is used in diverse conservation applications, including evaluating management effectiveness, relative risk of threats, and potential changes to protective status (Beissinger & McCullough, 2002 ), and can be a critical tool for making decisions with imperfect knowledge of the system state, often on limited timelines (Meine et al., 2006 ). Chaudhary and Oli ( 2020 ) recently developed a framework to appraise the quality of PVAs based on the presence of essential background, model, and analysis components. They evaluated 160 published PVAs and reported a decline in the quality of PVAs over time (1990−2017). We agree PVA studies should report unambiguous descriptions of their essential components (Table 1 in Chaudhary and Oli) and explicitly state the model's biological and statistical assumptions. The need for increased transparency in PVAs is evident. Morrison et al. ( 2016 ) reported that only 50% of PVAs published in peer-reviewed and gray literature were both reproducible and repeatable. Further, in an examination of 67 studies that used matrix population models (widely used in PVAs), Kendall et al. ( 2019 ) reported that models frequently contained misspecification errors. Given the rapid advancement of simulation techniques, updated guidance for PVA construction is warranted. However, we believe the essential PVA components identified by Chaudhary and Oli contain a critical omission: the decision context in which the PVA was created and its usefulness in that context. Quality and utility are not mutually exclusive; however, some models that do not meet idealized quality standards might still be valuable because they are useful and represent the best available science for a given decision context (hereafter, decision-support models). The definition of quality for decision-support models should be different than models developed for the purpose of learning (hereafter, heuristic models) and should incorporate how useful the model was, despite information gaps. We further argue that assessment questions should be used prospectively to guide modeling projects, rather than for retrospective comparison of model quality.

Conservation Biology↗

Spatial proximity moderates genotype uncertainty in genetic tagging studies

Accelerating declines of an increasing number of animal populations worldwide necessitate methods to reliably and efficiently estimate demographic parameters such as population density and trajectory. Standard methods for estimating demographic parameters from noninvasive genetic samples are inefficient because lower-quality samples cannot be used, and they assume individuals are identified without error. We introduce the genotype spatial partial identity model (gSPIM), which integrates a genetic classification model with a spatial population model to combine both spatial and genetic information, thus reducing genotype uncertainty and increasing the precision of demographic parameter estimates. We apply this model to data from a study of fishers ( Pekania pennanti ) in which 37% of hair samples were originally discarded because of uncertainty in individual identity. The gSPIM density estimate using all collected samples was 25% more precise than the original density estimate, and the model identified and corrected three errors in the original individual identity assignments. A simulation study demonstrated that our model increased the accuracy and precision of density estimates 63 and 42%, respectively, using three replicated assignments (e.g., PCRs for microsatellites) per genetic sample. Further, the simulations showed that the gSPIM model parameters are identifiable with only one replicated assignment per sample and that accuracy and precision are relatively insensitive to the number of replicated assignments for high-quality samples. Current genotyping protocols devote the majority of resources to replicating and confirming high-quality samples, but when using the gSPIM, genotyping protocols could be more efficient by devoting more resources to low-quality samples.

Proceedings of the National Academy of Sciences↗

Urban contributions of glyphosate and its degradate AMPA to streams in the United States

Glyphosate is the most widely used herbicide in the world, being routinely applied to control weeds in both agricultural and urban settings. Microbial degradation of glyphosate produces aminomethyl phosphonic acid (AMPA). The high polarity and water-solubility of glyphosate and AMPA has, until recently, made their analysis in water samples problematic. Thus, compared to other herbicides (e.g. atrazine) there are relatively few studies on the environmental occurrence of glyphosate and AMPA. In 2002, treated effluent samples were collected from 10 wastewater treatment plants (WWTPs) to study the occurrence of glyphosate and AMPA. Stream samples were collected upstream and downstream of the 10 WWTPs. Two reference streams were also sampled. The results document the apparent contribution of WWTP effluent to stream concentrations of glyphosate and AMPA, with roughly a two-fold increase in their frequencies of detection between stream samples collected upstream and those collected downstream of the WWTPs. Thus, urban use of glyphosate contributes to glyphosate and AMPA concentrations in streams in the United States. Overall, AMPA was detected much more frequently (67.5%) compared to glyphosate (17.5%).

Science of the Total Environment↗