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Assessing trade-offs in developing a landscape-scale nest monitoring programme for a threatened shorebird

Effective monitoring of wildlife species requires thorough planning and development of survey programmes that can address management and conservation objectives. Decisions about monitoring programmes include where to survey, survey design and how much effort to allocate at survey sites are typically predicated on limited budgets and available resources. When the scope of inference requires monitoring on a broad spatial scale, predictions of habitat distribution or suitability may be useful for identifying potential survey sites. We focused on a threatened but widely distributed shorebird, the piping plover ( Charadrius melodus ), which is actively monitored across some, but not all of its range. Our objective was to use piping plover habitat distribution maps, which vary annually, to assess the effectiveness of multiple monitoring programme scenarios and their associated costs. In the breeding range, efforts to improve productivity for species of conservation concern often focus on improving probabilities of nest survival. Consequently, collecting adequate nesting data is crucial for obtaining accurate and precise estimates of nest survival and for evaluating the effectiveness of management actions. By simulating the nest monitoring process, we evaluated how much area, where and how often to survey each site when estimating nest survival and detecting effects of potential management actions. As expected, precision increased and bias decreased around nest survival estimates with greater survey coverage and nest visit frequency. We also identified monitoring programmes with negative net values where survey costs outweighed statistical benefits. Although we applied our simulation framework to evaluate nest monitoring designs for piping plovers, it could be extended to assess whether different monitoring programmes can detect changes in the distribution of other species or occupancy of habitats over time.

Ecological Solutions and Evidence↗

A 30-m landsat-derived cropland extent product of Australia and China using random forest machine learning algorithm on Google Earth Engine cloud computing platform

Mapping high resolution (30-m or better) cropland extent over very large areas such as continents or large countries or regions accurately, precisely, repeatedly, and rapidly is of great importance for addressing the global food and water security challenges. Such cropland extent products capture individual farm fields, small or large, and are crucial for developing accurate higher-level cropland products such as cropping intensities, crop types, crop watering methods (irrigated or rainfed), crop productivity, and crop water productivity. It also brings many challenges that include handling massively large data volumes, computing power, and collecting resource intensive reference training and validation data over complex geographic and political boundaries. Thereby, this study developed a precise and accurate Landsat 30-m derived cropland extent product for two very important, distinct, diverse, and large countries: Australia and China. The study used of eight bands (blue, green, red, NIR, SWIR1, SWIR2, TIR1, and NDVI) of Landsat-8 every 16-day Operational Land Imager (OLI) data for the years 2013–2015. The classification was performed by using a pixel-based supervised random forest (RF) machine learning algorithm (MLA) executed on the Google Earth Engine (GEE) cloud computing platform. Each band was time-composited over 4–6 time-periods over a year using median value for various agro-ecological zones (AEZs) of Australia and China. This resulted in a 32–48-layer mega-file data-cube (MFDC) for each of the AEZs. Reference training and validation data were gathered from: (a) field visits, (b) sub-meter to 5-m very high spatial resolution imagery (VHRI) data, and (c) ancillary sources such as from the National agriculture bureaus. Croplands versus non-croplands knowledge base for training the RF algorithm were derived from MFDC using 958 reference-training samples for Australia and 2130 reference-training samples for China. The resulting 30-m cropland extent product was assessed for accuracies using independent validation samples: 900 for Australia and 1972 for China. The 30-m cropland extent product of Australia showed an overall accuracy of 97.6% with a producer’s accuracy of 98.8% (errors of omissions = 1.2%), and user’s accuracy of 79% (errors of commissions = 21%) for the cropland class. For China, overall accuracies were 94% with a producer’s accuracy of 80% (errors of omissions = 20%), and user’s accuracy of 84.2% (errors of commissions = 15.8%) for cropland class. Total cropland areas of Australia were estimated as 35.1 million hectares and 165.2 million hectares for China. These estimates were higher by 8.6% for Australia and 3.9% for China when compared with the traditionally derived national statistics. The cropland extent product further demonstrated the ability to estimate sub-national cropland areas accurately by providing an R 2 value of 0.85 when compared with province-wise cropland areas of China. The study provides a paradigm-shift on how cropland maps are produced using multi-date remote sensing. These products can be browsed at www.croplands.org and made available for download at NASA’s Land Processes Distributed Active Archive Center (LP DAAC) https://www.lpdaac.usgs.gov/node/1282 .

ISPRS Journal of Photogrammetry and Remote Sensing↗

Predictions of future ephemeral springtime waterbird stopover habitat availability under global change

In the present period of rapid, worldwide change in climate and landuse (i.e., global change), successful biodiversity conservation warrants proactive management responses, especially for long-distance migratory species. However, the development and implementation of management strategies can be impeded by high levels of uncertainty and low levels of control over potentially impactful future events and their effects. Scenario planning and modeling are useful tools for expanding perspectives and informing decisions under these conditions. We coupled scenario planning and statistical modeling to explain and predict playa wetland inundation (i.e., presence/absence of water) and ponded area (i.e., extent of water) in the Rainwater Basin, an anthropogenically altered landscape that provides critical stopover habitat for migratory waterbirds. Inundation and ponded area models for total wetlands, those embedded in rowcrop fields, and those not embedded in rowcrop fields were trained and tested with wetland ponding data from 2004 and 2006–2009, and then used to make additional predictions under two alternative climate change scenarios for the year 2050, yielding a total of six predictive models and 18 prediction sets. Model performance ranged from moderate to good, with inundation models outperforming ponded area models, and models for non-rowcrop-embedded wetlands outperforming models for total wetlands and rowcrop-embedded wetlands. Model predictions indicate that if the temperature and precipitation changes assumed under our climate change scenarios occur, wetland stopover habitat availability in the Rainwater Basin could decrease in the future. The results of this and similar studies could be aggregated to increase knowledge about the potential spatial and temporal distributions of future stopover habitat along migration corridors, and to develop and prioritize multi-scale management actions aimed at mitigating the detrimental effects of global change on migratory waterbird populations.

Nebraska↗

Geographic Information System Software to Remodel Population Data Using Dasymetric Mapping Methods

The U.S. Census Bureau provides decadal demographic data collected at the household level and aggregated to larger enumeration units for anonymity purposes. Although this system is appropriate for the dissemination of large amounts of national demographic data, often the boundaries of the enumeration units do not reflect the distribution of the underlying statistical phenomena. Conventional mapping methods such as choropleth mapping, are primarily employed due to their ease of use. However, the analytical drawbacks of choropleth methods are well known ranging from (1) the artificial transition of population at the boundaries of mapping units to (2) the assumption that the phenomena is evenly distributed across the enumeration unit (when in actuality there can be significant variation). Many methods to map population distribution have been practiced in geographic information systems (GIS) and remote sensing fields. Many cartographers prefer dasymetric mapping to map population because of its ability to more accurately distribute data over geographic space. Similar to ?choropleth maps?, a dasymetric map utilizes standardized data (for example, census data). However, rather than using arbitrary enumeration zones to symbolize population distribution, a dasymetric approach introduces ancillary information to redistribute the standardized data into zones relative to land use and land cover (LULC), taking into consideration actual changing densities within the boundaries of the enumeration unit. Thus, new zones are created that correlate to the function of the map, capturing spatial variations in population density. The transfer of data from census enumeration units to ancillary-driven homogenous zones is performed by a process called areal interpolation.

Techniques and Methods↗

A survey of benthic sediment contaminants in reaches of the Columbia River Estuary based on channel sedimentation characteristics

While previous studies have documented contaminants in fish, sediments, water, and wildlife, few specifics are known about the spatial distribution of contaminants in the Columbia River Estuary (CRE). Our study goal was to characterize sediment contaminant detections and concentrations in reaches of the CRE that were concurrently being sampled to assess contaminants in water, invertebrates, fish, and osprey (Pandion haliaetus) eggs. Our objectives were to develop a survey design based on sedimentation characteristics and then assess whether sediment grain size, total organic carbon (TOC), and contaminant concentrations and detections varied between areas with different sedimentation characteristics. We used a sediment transport model to predict sedimentation characteristics of three 16 km river reaches in the CRE. We then compartmentalized the modeled change in bed mass after a two week simulation to define sampling strata with depositional, stable, or erosional conditions. We collected and analyzed bottom sediments to assess whether substrate composition, organic matter composition, and contaminant concentrations and detections varied among strata within and between the reaches. We observed differences in grain size fractions between strata within and between reaches. We found that the fine sediment fraction was positively correlated with TOC. Contaminant concentrations were statistically different between depositional vs. erosional strata for the industrial compounds, personal care products and polycyclic aromatic hydrocarbons class (Indus–PCP–PAH). We also observed significant differences between strata in the number of detections of Indus–PCP–PAH (depositional vs. erosional; stable vs. erosional) and for the flame retardants, polychlorinated biphenyls, and pesticides class (depositional vs. erosional, depositional vs. stable). When we estimated mean contaminant concentrations by reach, we observed higher contaminant concentrations in the furthest downstream reach with a decreasing trend in the two upstream reaches. Contaminant survey designs that account for sedimentation characteristics could increase the probability that sampling is allocated to areas likely to be contaminated.

Columbia River Estuary↗

A database of lotic invertebrate traits for North America

The assessment and study of stream communities may be enhanced if functional characteristics such as life-history, habitat preference, and reproductive strategy were more widely available for specific taxa. Species traits can be used to develop these functional indicators because many traits directly link functional roles of organisms with controlling environmental factors (for example, flow, substratum, temperature). In addition, some functional traits may not be constrained by taxonomy and are thus applicable at multiple spatial scales. Unfortunately, a comprehensive summary of traits for North American invertebrate taxa does not exist. Consequently, the U.S. Geological Survey's National Water-Quality Assessment Program in cooperation with Colorado State University compiled a database of traits for North American invertebrates. A total of 14,127 records for over 2,200 species, 1,165 genera, and 249 families have been entered into the database from 967 publications, texts and reports. Quality-assurance procedures indicated error rates of less than 3 percent in the data entry process. Species trait information was most complete for insect taxa. Traits describing resource acquisition and habitat preferences were most frequently reported, whereas those describing physiological tolerances and reproductive biology were the least frequently reported in the literature. The database is not exhaustive of the literature for North American invertebrates and is biased towards aquatic insects, but it represents a first attempt to compile traits in a web-accessible database. This report describes the database and discusses important decisions necessary for identifying ecologically relevant, environmentally sensitive, non-redundant, and statistically tractable traits for use in bioassessment programs.

Data Series↗

Nearshore sediment monitoring for the Stormwater Action Monitoring (SAM) Program, Puget Sound, western Washington

Chemicals such as metals and organics (polychlorinated biphenyl [PCBs], polybrominated diphenyl ethers [PBDEs], polycyclic aromatic hydrocarbons [PAHs], and phthalates) continue to enter Puget Sound, western Washington, from point sources (such as industrial and municipal outfalls) and combined sewer outfalls and non-point sources (such as stormwater runoff). Runoff during storm events has been identified as a major source of contamination entering Puget Sound and has been implicated in the degradation of nearshore habitats and biota. Metals, organic chemicals, and other pollutants are known to accumulate in sediments such as those present along the shoreline of Puget Sound. In addition to chemical contaminants, small plastic particles (known as microplastics), found in marine waters of Puget Sound and suspected of being in aquatic sediments, are a potential concern because they can be ingested by animals and are suspected of transporting sorbed chemicals such as PCBs and metals. The Stormwater Work Group of Puget Sound (SWG) (composed of State and municipal stormwater permittees, and other stakeholders) developed a strategy to address sediment conditions in the nearshore environment of Puget Sound. As part of this strategy, the SWG developed a regional stormwater monitoring strategy designed to inform monitoring requirements in National Pollutant Discharge Elimination System (NPDES) stormwater permits issued by the Washington State Department of Ecology (Ecology). The monitoring program is referred to as the Stormwater Action Monitoring (SAM). The overall focus of the work described in this report is to address one of the goals of SAM, which is to characterize the status, spatial extent, and quality of Puget Sound sediment chemicals in the nearshore urban areas. The nearshore urban areas are defined as areas parallel to established Urban Growth Areas (UGAs) using a spatially balanced probabilistic Generalized Random Tessellation Stratified (GRTS) sampling design. One of the benefits of the GRTS sampling design used for this study is that it allows one to efficiently extrapolate from a relatively small number of sampled nearshore sites to the entire nearshore shoreline within the 2011 defined UGA boundaries of Puget Sound. In addition to characterizing nearshore sediment chemical concentrations, this study also characterized the abundance of microplastics in the nearshore sediment. A total of 41 randomly selected sites were sampled throughout Puget Sound in summer and early autumn of 2016. All sampling sites were located at 6 feet below the Mean Lower Low Water line. The top 2–3 centimeters of sediment were collected using a boat-mounted, pre-cleaned stainless-steel box corer. All chemical samples were sieved to 2 millimeters and placed in appropriate containers for chemical analysis for PCBs, PBDEs, PAHs, phthalates, metals, total organic carbon, and grain size. Pre-sieved sediment samples were stored in glass containers for microplastic analysis. Nearshore sediment chemical concentrations were summarized using numerous statistical approaches to examine the minimum, mean, and maximum concentrations for each of the compounds analyzed and to compare the results to criteria and other nearshore and marine sediment studies. The GRTS sampling design also allowed the authors to assess the percentage of the UGA nearshore environment that did not meet established standards or criteria for each chemical analyzed. Additionally, regression and machine learning statistical analyses were used to examine relations between measured chemical concentrations, and land cover and geologic features at multiple scales within the watersheds adjacent to sampling sites. The influence of marine hydrodynamic factors on nearshore sediment chemical concentrations was statistically evaluated with nonparametric methods by assigning each sampling site to one of five nearshore drift cell types based on its location. The Puget Sound shoreline can be divided into segments, referred to as drift cells, based on the movement of sediment along the shore by waves. Each drift cell type has a unique influence on nearshore sediment transport. The nearshore sediment chemical concentrations for organics and metals generally were low, and in most cases less than Washington State criteria. The concentrations of some PAHs were greater than the criteria, but these exceedances were limited to one or two sites. The results of the probabilistic study design determined that, for the PAHs examined, 96 percent or more of the 1,344 km of shoreline represented by this study had concentrations less than any established criteria. For the remaining organics (PCBs and PBDEs), the probabilistic study design indicates that more than 98 percent of shoreline examined had concentrations less than criteria or proposed standards. For the metals, the results of the study indicate that 100 percent of the nearshore sediment had concentrations less than the criteria. The relations between sediment organic and metal concentrations, and adjacent watershed land cover and the particle size of the samples, were determined to be weakly related. Although weakly related, the particle size of the sediment in a sample typically explained more of the variation in metal concentrations than organics. While the measured watershed attributes adjacent to the sampling sites and sediment size of the samples were weakly related to chemical concentrations, they were significantly related to unique drift cells along the shoreline of Puget Sound known as drift cells. Each drift cell represents a long-term directional transport of sediment from its source to its depositional zone. Sediment chemical concentrations were significantly higher in drift cells with limited sediment movement compared to those with higher sediment transport energy. Microplastics in the nearshore sediment ranged from 0.02 to 0.65 pieces per gram of sediment, with a mean of 0.19 pieces per gram of sediment, and were dominated by small fibers (355–1,000 micrometers). Like chemical concentrations, microplastics concentrations in the nearshore sediment were poorly related to watershed land cover. Although not significantly different, microplastics concentrations generally were higher in the low energy drift cells compared to the high energy drift cells. The results of this study provide a statistically valid status assessment of current nearshore sediment chemical conditions throughout Puget Sound in those areas adjacent to defined UGAs. In addition to the study findings of relatively low concentrations of PCBs, PBDEs, PAHs, phthalates, and metals, the study design provides a statistically valid tool for evaluating changes in these compounds over time if future nearshore sediment assessments are done. Furthermore, the assessment of microplastic abundance represents the first study of its kind that can be used as a benchmark for future evaluations. The results of this study will help inform Ecology in the implementation of monitoring requirements as part of its NPDES stormwater permitting process.

Washington↗

Backpack satellite transmitters reduce survival but not nesting propensity or success of greater sage-grouse

Telemetry technology is ubiquitous for studying the behavior and demography of wildlife, including the use of traditional very high frequency (VHF) radio telemetry and more recent methods that record animal locations using global positioning systems (GPS). Satellite-based GPS telemetry allows researchers to collect high spatial–temporal resolution data remotely but may also come with additional costs. For example, recent studies from the southern Great Basin suggested GPS transmitters attached via backpacks may reduce the survival of greater sage-grouse ( Centrocercus urophasianus ) relative to VHF transmitters attached via collars that have been in use for decades. While some evidence suggests GPS backpacks reduce survival, no studies have examined the effects of GPS backpacks on breeding behavior and success. Therefore, we compared survival, breeding behavior, and nest success of sage-grouse hens marked with both VHF collars and GPS backpack transmitter over a 7-year period in central Idaho, USA. GPS backpacks reduced spring–summer survival of sage-grouse hens relative to hens with VHF collars, where daily mortality probability was 68%–82% higher from March 1 to August 1. Yet satellite GPS backpacks did not consistently affect nest success or the likelihood or timing of nest initiation relative to VHF collars. Daily nest survival varied annually and with timing of nest initiation and nest age, but marginal effects of transmitter type were statistically insignificant and interactions between transmitter type and study year produced no meaningful patterns. Our results corroborate recent studies for the effect of satellite GPS backpacks on sage-grouse survival, but also suggest that these transmitters do not appear to affect components of fecundity. Our results therefore add important context to recent debate surrounding the effects of GPS backpacks on sage-grouse, and the relative strengths and weaknesses of different transmitter types for understanding behavior and population dynamics.

Idaho↗

Detecting sea-level hazards: Simple regression-based methods for calculating the acceleration of sea level

This report documents the development of statistical tools used to quantify the hazard presented by the response of sea-level elevation to natural or anthropogenic changes in climate and ocean circulation. A hazard is a physical process (or processes) that, when combined with vulnerability (or susceptibility to the hazard), results in risk. This study presents the development and comparison of new and existing sea-level analysis methods, exploration of the strengths and weaknesses of the methods using synthetic time series, and when appropriate, synthesis of the application of the method to observed sea-level time series. These reports are intended to enhance material presented in peer-reviewed journal articles where it is not always possible to provide the level of detail that might be necessary to fully support or recreate published results. The purpose of this report is to document and compare three simple methodologies that have previously been used to provide estimates with associated errors of the acceleration of sea-level elevation. These techniques have been used by coastal scientists and planners in assessing coastal risk over a wide range of spatial and temporal scales. Because relative sea-level (SL) elevation time series contain energetic fluctuations at many time scales, extracting what can be relatively small rate and acceleration signals (along with estimates of the error) from much larger “noise” has proven to be both difficult and controversial. Acceleration is a preferred measure of SL response to recent changes in the Earth’s climate because over time scales of 100 years or less slow vertical land motions (such as glacial isostatic adjustment) contribute only to the linear signal and not to acceleration, thus reducing the complexity of the analysis. Hence acceleration is useful if the goal of a study is to characterize and quantify the hazard associated with the changing relative elevation of water with respect to land on decadal time scales. Although in some cases it may be necessary to determine the cause of relative sea level rise, as a first step, it is important to accurately estimate the magnitude of the threat. Most researchers agree that global sea level (GSL) rose persistently through much of the 20th century at about 1.5–2.0 millimeters per year (mm/yr). There is far less agreement about whether the rate of sea-level rise (SLR) is increasing (that is, an acceleration in SL). Recent studies, and most of their predecessors, use tide gage data to quantify SL acceleration, A SL (t). In the current study, three techniques were used to calculate acceleration from tide gage data, and of those examined, it was determined that the two techniques based on sliding a regression window through the time series are more robust compared to the technique that fits a single quadratic form to the entire time series, particularly if there is temporal variation in the magnitude of the acceleration. The single-fit quadratic regression method has been the most commonly used technique in determining acceleration in tide gage data. The inability of the single-fit method to account for time-varying acceleration may explain some of the inconsistent findings between investigators. Properly quantifying A SL (t) from field measurements is of particular importance in evaluating numerical models of past, present, and future SLR resulting from anticipated climate change.

Open-File Report↗

Nitrate and selected pesticides in ground water of the Mid-Atlantic region

Data from more than 850 sites were compiled and analyzed to document the occurrence of nitrate and pesticides in ground water of the Mid-Atlantic region as part of the Mid-Atlantic Integrated Assessment program of the U.S. Environmental Protection Agency. Only those data collected by the U.S. Geological Survey as part of regional networks between October 1985 and September 1996 (inclusive) were used in the analyses, and the data were examined to ensure analytical results are not biased toward sites at the same location or sites sampled multiple times during this period. Regional data are available for most of the Mid-Atlantic region but large spatial gaps in available data do exist. Nitrate was detected in nearly three-quarters of the samples for which it was analyzed, commonly at levels that suggest anthropogenic sources. Ten percent of samples contained nitrate at concentrations exceeding the Federal Maximum Contaminant Level (MCL) of 10 milligrams per liter as nitrogen. Pesticide compounds (including atrazine, metolachlor, prometon, simazine, and desethylatrazine, an atrazine degradate) were detected in about half of the samples for which they were analyzed, but rarely at concentrations exceeding established MCL?s. The most commonly detected pesticide compounds were desethylatrazine and atrazine. The occurrence of nitrate and pesticides in ground water of the Mid-Atlantic region is related to land cover and rock type. Likely sources of nitrate and pesticides to ground water include agricultural and urban land-use practices; rock type affects the movement of these compounds into and through the ground-water system. Nitrate concentrations in the compiled data set are significantly higher in ground water in agricultural areas than in urban or forested areas, but concentrations in areas of row crops are statistically indistinguishable from those in areas of pastures. Detection frequencies of atrazine, desethylatrazine, and simazine are indistinguishable among urban areas, row crops, and pastures. Prometon was most commonly detected in ground water in urban areas. Ground-water samples from forested areas typically contained the lowest concentrations of nitrate and detection frequencies of pesticides. Concentrations of nitrate and detection frequencies of pesticides were significantly higher in samples from carbonate rocks than in those from any other rock type. Most areas of the Mid-Atlantic region that are underlain by carbonate rocks have been developed for agricultural or urban use and the solution channels that are typical of carbonate rocks allow for relatively rapid transport of surficial contaminants throughout the ground-water system. Nitrate concentrations in unconsolidated aquifers were among the lowest for all rock types, possibly because of denitrification in organic-rich subsoils and shallow sediments.

Water-Resources Investigations Report↗

Tabulated Transmissivity and Storage Properties of the Floridan Aquifer System in Florida and Parts of Georgia, South Carolina, and Alabama

A goal of the U.S. Geological Survey Groundwater Resources Program is to assess the availability of fresh water within each of the principal aquifers in the United States with the greatest groundwater withdrawals. The Floridan aquifer system (FAS), which covers an area of approximately 100,000 square miles in Florida and parts of Georgia, Alabama, Mississippi, and South Carolina, is one such principal aquifer, having the fifth largest groundwater withdrawals in the Nation, totaling 3.64 billion gallons per day in 2000. Compilation of FAS hydraulic properties is critical to the development and calibration of groundwater flow models that can be used to develop water budgets spatially and temporally, as well as to evaluate resource changes over time. Wells with aquifer test data were identified as Upper Floridan aquifer (UFA), Lower Floridan aquifer (LFA), Floridan aquifer system (FAS, Upper Floridan with some middle and/or Lower Floridan), or middle Floridan confining unit (MCU), based on the identification from the original database or report description, or comparison of the open interval of the well with previously published maps. This report consolidates aquifer hydraulic property data obtained from multiple databases and reports of the U.S. Geological Survey, various State agencies, and the Water Management Districts of Florida, that are compiled into tables to provide a single information source for transmissivity and storage properties of the FAS as of October 2011. Transmissivity calculated from aquifer pumping tests and specific-capacity data are included. Values for transmissivity and storage coefficients are intended for use in regional or sub regional groundwater flow models; thus, any tests (aquifer pumping tests and specific capacity data) that were conducted with packers or for open intervals less than 30 feet in length are excluded from the summary statistics and tables of this report, but are included in the database. The transmissivity distribution from the aquifer pumping tests is highly variable. The transmissivity based on aquifer pumping tests (from 1,045 values for the UFA and FAS) ranges from 8 to about 9,300,000 square feet per day (ft 2 /d) and values of storage coefficient (646 reported) range from 3x10 -9 to 0.41. The 64 transmissivity values for the LFA range from about 130 to 4,500,000 ft 2 /d, and the 17 storage coefficient values range from 7x10 -8 to 0.03. The 14 transmissivity values for the MCU range from 1 to about 600,000 ft 2 /d and the 10 storage coefficient values range from 8x10 -8 to 0.03. Transmissivity estimates for the UFA and FAS for 442 specific capacity tests range from approximately 200 to 1,000,000 ft 2 /d.

Alabama, Florida, Georgia, South Carolina↗

Discharge magnitude drives interannual variation in distribution of the invertebrate host Manayunkia occidentalis of the salmon parasite Ceratonova shasta

Objective The objective of this study was to evaluate statistical evidence for relationships between flow event characteristics and annelid host distribution, an important and necessary step toward providing and justifying management actions. Declines in Klamath River salmon have been attributed to infection and disease that are caused by the myxozoan parasite Ceratonova shasta . Flow manipulation has been used to manage risk of C. shasta for juvenile salmonids in this system. One mechanism by which flow-related disturbance can reduce the risk of C. shasta infection for salmon is by reducing populations of the obligate invertebrate host Manayunkia occidentalis . We previously demonstrated that hydraulic conditions during peak discharge events drive the distribution of M. occidentalis and suggested that high-magnitude flow events would be effective for reducing the distribution of the annelid host. However, evidence of the effects of flow events on M. occidentalis was needed to support the use of flow management. Methods To address this knowledge gap, we leveraged a multiyear data set to estimate relationships between the distribution the annelid host and the characteristics of each discharge event. We measured the presence or absence of M. occidentalis at spatially georeferenced sampling locations, stratified across the range of hydraulic and substrate conditions in three reaches annually from 2012 to 2020. Results During the study period, the magnitude of peak discharge ranged from 52.4 to 314.3 m 3 /s. The inclusion of seven additional years’ data in the base model (hierarchical; annual-level covariate + previous “single year” model) resulted in parameter estimates that were similar to those that were derived for the previous (2016) model, supporting that substrate, depth, and velocity during peak discharge predicted annelid distribution. The magnitude model (base model + annual-level covariate for peak discharge) showed evidence of a strong negative association with annelid presence (95% of all Markov chain–Monte Carlo draws were negative). Every 101.9 m 3 /s increase in peak discharge was associated with an estimated 39% decrease in the odds of annelid presence. The estimated effect of magnitude on the probability of annelid presence was illustrated in the contrast between low- and high-magnitude peak discharge scenarios. For both scenarios, the effects of depth, velocity at peak discharge, and substrate, consistent with the previous model (2016), were evident, as was the further reduction in probability of annelid presence at the higher peak discharge. However, under the low-magnitude discharge scenario, M. occidentalis were predicted to be present on smaller less stable substrates and at a wider range of depths and velocities than they were under the high-magnitude discharge scenario. In contrast to the covariate for magnitude, the inclusion of a duration covariate did not show a strong relationship with annelid distribution, which we attributed to the lack of variation in this covariate during the study period. Conclusions This work provides quantitative evidence that high-magnitude peak discharge flow events lead to lower probabilities of annelid host presence. Lower probabilities of annelid hosts are indicative of a reduced distribution of the M. occidentalis host and in turn reduced risk of C. shasta for salmon.

California↗

Controls of the spatial variability of denitrification potential in nontidal floodplains of the Chesapeake Bay watershed, USA

Identifying floodplains with high rates of denitrification will help prioritize restoration projects for the removal of nitrogen. Currently, relationships of denitrification with hydrogeomorphic, physiographic, and climate ( i.e. , largescale) characteristics of floodplains are relatively unknown, even though these characteristics have datasets ( e.g. , geographic mapping tools) that are publicly available (or soon-to-become) that could be used to understand denitrification variability. Thus, we investigated control of denitrification by these largescale characteristics in eighteen nontidal floodplains of the Chesapeake Bay watershed ( i.e. , at regional scale, >100 km, scale), using measurements or compiled data at the scales of the stream reach and respective catchment; floodplain soil and herbaceous vegetation ( i.e. , local) characteristics were additionally investigated. Soil denitrification potentials were measured in May, July, and August using complementary acetylene-based techniques under an anoxic environment. Linear largescale predictors of denitrification potential measurements included stream nitrogen and phosphorus concentrations (+), channel width-to-depth ratio (+), floodplain sedimentation (+), forested (−) and urban (+) catchment land cover, and seasonal air temperature (−). Three predictors, catchment forested land cover (strongly related to agricultural land cover), catchment urban land cover, and floodplain sedimentation were related to the most number of denitrification potential measurements. Soil structure, soil nutrient concentrations, and herbaceous vegetation characteristics that were seasonally measured (with a few exceptions) were linear predictors of denitrification potentials in May and August, with nitrogen and carbon characteristics the most consistent (positive) predictors across measurements. Nutrient amendment assays further supported the importance of nitrogen and carbon controls. Using the local characteristics as statistical mediators in path analysis, greater non-forested catchment land cover indirectly increased denitrification through greater floodplain soil nitrate, total phosphorus, and herbaceous aboveground biomass. Additionally, greater floodplain sedimentation indirectly increased denitrification through greater soil pH, total phosphorus, and potential carbon mineralization. Due to the consistency of relationships across denitrification potential measurements along with path modeling results, hotspots of floodplain denitrification should be found in urban and agricultural catchments where river-floodplain hydrologic connectivity promotes sedimentation. Largescale predictors explained 43–57% of the variation in denitrification potentials and should be useful for prediction in floodplains. Siting restoration projects in watersheds for maximum nitrate removal using publicly available largescale datasets is both feasible and effective.

Chesapeake Bay watershed↗

Numbers of wildlife fatalities at renewable energy facilities in a targeted development region

Increased interest in renewable energy has fostered development of wind and solar energy facilities globally. However, energy development sometimes has negative environmental impacts, such as wildlife fatalities. Efforts by regional land managers to balance energy potential while minimizing fatality risk currently rely on datasets that are aggregated at continental, but not regional scales, that focus on single species, or that implement meta-analyses that inappropriately use inferential statistics. We compiled and summarized fatality data from 87 reports for solar and wind facilities in the Mojave and Sonoran Deserts region of southern California within the Desert Renewable Energy Conservation Plan area. Our goal was to evaluate potential temporal and guild-specific patterns in fatalities, especially for priority species of conservation concern. We also aimed to provide a perspective on approaches interpreting these types of data, given inherent limitations in how they were collected. Mourning doves ( Zenaida macroura ), Chukar ( Alectoris chukar ) and California Quail ( Callipepla californica ), and passerines ( Passeriformes ), accounted for the most commonly reported fatalities. However, our aggregated count data were derived from raw, uncorrected totals, and thus reflect an absolute minimum number of fatalities for the monitored period. Additionally, patterns in the raw data suggested that many species commonly documented as fatalities (e.g., waterbirds and other nocturnal migrants, bats) are rarely counted during typical pre-construction use surveys. This may explain the more commonly observed mismatch between pre-construction risk assessment and actual fatalities. Our work may serve to guide design of future scientific research to address temporal and spatial patterns in fatalities and to apply rigorous guild-specific survey methodologies to estimate populations at risk from renewable energy development.

California↗

The epipelagic fish community of Beaufort Sea coastal waters, Alaska

A three-year study of epipelagic fishes inhabiting Beaufort Sea coastal waters in Alaska documented spatial and temporal patterns in fish distribution and abundance and examined their relationships to thermohaline features during summer. Significant interannual, seasonal, and geographical differences in surface water temperatures and salinities were observed. In 1990, sea ice was absent and marine conditions prevailed, whereas in 1988 and 1991, heavy pack ice was present and the dissolution of the brackish water mass along the coast proceeded more slowly. Arctic cod, capelin, and liparids were the most abundant marine fishes in the catches, while arctic cisco was the only abundant diadromous freshwater species. Age-0 arctic cod were exceptionally abundant and large in 1990, while age-0 capelin dominated in the other years. The alternating numerical dominances of arctic cod and age-0 capelin may represent differing species' responses to wind-driven oceanographic processes affecting growth and survival. The only captures of age-0 arctic cisco occurred during 1990. Catch patterns indicate they use a broad coastal migratory corridor and tolerate high salinities. As in the oceanographic data, geographical and temporal patterns were apparent in the fish catch data, but in most cases these patterns were not statistically testable because of excessive zero catches. The negative binomial distribution appeared to be a suitable statistical descriptor of the aggregated catch patterns for the more common species.

Alaska↗

Kinematic ground motion simulations on rough faults including effects of 3D stochastic velocity perturbations

We describe a methodology for generating kinematic earthquake ruptures for use in 3D ground‐motion simulations over the 0–5 Hz frequency band. Our approach begins by specifying a spatially random slip distribution that has a roughly wavenumber‐squared fall‐off. Given a hypocenter, the rupture speed is specified to average about 75%–80% of the local shear wavespeed and the prescribed slip‐rate function has a Kostrov‐like shape with a fault‐averaged rise time that scales self‐similarly with the seismic moment. Both the rupture time and rise time include significant local perturbations across the fault surface specified by spatially random fields that are partially correlated with the underlying slip distribution. We represent velocity‐strengthening fault zones in the shallow (<5 km) and deep (>15 km) crust by decreasing rupture speed and increasing rise time in these regions. Additional refinements to this approach include the incorporation of geometric perturbations to the fault surface, 3D stochastic correlated perturbations to the P ‐ and S ‐wave velocity structure, and a damage zone surrounding the shallow fault surface characterized by a 30% reduction in seismic velocity. We demonstrate the approach using a suite of simulations for a hypothetical M w 6.45 strike‐slip earthquake embedded in a generalized hard‐rock velocity structure. The simulation results are compared with the median predictions from the 2014 Next Generation Attenuation‐West2 Project ground‐motion prediction equations and show very good agreement over the frequency band 0.1–5 Hz for distances out to 25 km from the fault. Additionally, the newly added features act to reduce the coherency of the radiated higher frequency ( f >1 Hz) ground motions, and homogenize radiation‐pattern effects in this same bandwidth, which move the simulations closer to the statistical characteristics of observed motions as illustrated by comparison with recordings from the 1979 Imperial Valley earthquake.

Bulletin of the Seismological Society of America↗

ENSO-based outlook of droughts and agricultural outcomes in Afghanistan

Drought is one of the key drivers of food insecurity in Afghanistan, which is among the most food insecure countries in the world. In this study, we build on previous research and seek to answer the central question: “What is the influence of El Niño-Southern Oscillation (ENSO) on drought outlooks and agricultural yield outcome in Afghanistan, and how do these influences vary spatially ?” We do so by utilizing multiple indicators of droughts and available wheat yield reports. We find a clear distinction in the probability of drought (defined as being in the lower tercile) in Afghanistan during La Niña compared to El Niño events since 1981. The probability of drought in Afghanistan increased during La Niña, particularly in the North, Northeast, and West regions. La Niña events are related to an increase in the probability of snow drought, particularly in parts of the Amu Darya basin. It is found that relative to El Niño events, snow water equivalent [total runoff] during La Niña events January–March (March–July total runoff) decreases between 9% and 30% (28%–42%) for the five major basins in the country. The probability of agricultural drought during La Niña events is found to be higher than 70% in the rainfed and irrigated areas of the Northeast, North, and West regions. This result is at least partly supported by reported wheat yield composites related to La Niña events that tend to be lower than for El Niño events across all regions in the case of rainfed wheat (statistically significant in Northeast, West, and South regions) and in some cases for irrigated wheat. The results of this study have direct implications for improving early warning of worsening food insecurity in Afghanistan during La Niña events, given that we now have long-lead and skillful forecasts of ENSO up to 18–24 months in advance, which could potentially be used to provide earlier warning of worsening food insecurity in Afghanistan

Weather and Climate Extremes↗

Concentrations, and estimated loads and yields of nutrients and suspended sediment in the Little River basin, Kentucky, 2003-04

Nutrients, primarily nitrogen and phosphorus compounds, naturally occur but also are applied to land in the form of commercial fertilizers and livestock waste to enhance plant growth. Concentrations, estimated loads and yields, and sources of nitrite plus nitrate, total phosphorus, and orthophosphate were evaluated in streams of the Little River Basin to assist the Commonwealth of Kentucky in developing 'total maximum daily loads' (TMDLs) for streams in the basin. The Little River Basin encompasses about 600 square miles in Christian and Trigg Counties, and a portion of Caldwell County in western Kentucky. Water samples were collected in streams in the Little River Basin during 2003-04 as part of a study conducted in cooperation with the Kentucky Department of Agriculture. A total of 92 water samples were collected at four fixed-network sites from March through November 2003 and from February through November 2004. An additional 20 samples were collected at five synoptic-network sites during the same period. Median concentrations of nitrogen, phosphorus, and suspended sediment varied spatially and seasonally. Concentrations of nitrogen were higher in the spring (March-May) after fertilizer application and runoff. The highest concentration of nitrite plus nitrate-5.7 milligrams per liter (mg/L)-was detected at the South Fork Little River site. The Sinking Fork near Cadiz site had the highest median concentration of nitrite plus nitrate (4.6 mg/L). The North Fork Little River site and the Little River near Cadiz site had higher concentrations of orthophosphate in the fall and lower concentrations in the spring. Concentrations of orthophosphate remained high during the summer (June-August) at the North Fork Little River site possibly because of the contribution of wastewater effluent to streamflow. Fifty-eight percent of the concentrations of total phosphorus at the nine sites exceeded the U.S. Environmental Protection Agency recommended maximum concentration limit of 0.1 mg/L. Concentrations of suspended sediment were highest in the spring during runoff and lowest in the fall. The highest concentration of suspended sediment (1,020 mg/L) was observed at the Sinking Fork near Cadiz site. The median concentration of suspended sediment for all sites sampled was 12 mg/L. A nonparameteric statistical test (Wilcoxson rank-sum) showed that the median concentrations of suspended sediment were not different among any of the fixed-network sites. The Little River near Cadiz site contributed larger estimated mean annual loads of nitrite plus nitrate (2,500,000 pounds per year (lb/yr)) and total phosphorus (160,000 lb/yr) than the other three fixed-network sites. Of the two main upstream tributaries from the Little River near Cadiz site, the North Fork Little River was the greatest contributor of total phosphorus to the study area with an estimated mean annual load of 107,000 lb/yr or about 64 percent of the total estimated mean annual load at the Little River near Cadiz site. The other main upstream tributary, South Fork Little River, had an estimated mean annual load of total phosphorus that was about 20 percent of the mean annual load at the Little River near Cadiz site. Estimated loads of suspended sediment were largest at the Little River near Cadiz site, where the estimated mean annual load for 2003-04 was about 84,000,000 lb/yr. The North Fork Little River contributed an estimated 36 percent of the mean annual load of suspended sediment at the Little River near Cadiz site, while the South Fork Little River contributed an estimated 18 percent of the mean annual load at the Little River near Cadiz site. The North Fork Little River site had the largest estimated mean annual yield of total phosphorus (1,600 pounds per year per square mile (lb/yr/mi2)) and orthophosphate (1,100 lb/yr/mi2). A principal source of phosphorus for the North Fork Little River is discharge from wastewater-treatment facilities. The largest estimated mean annual yield of nitrite plus nitrate was observed at the South Fork Little River site. The North Fork Little River site had the largest estimated mean annual yield of suspended sediment (450,000 lb/yr/mi2). Inputs of nitrogen and phosphorus to streams from point and nonpoint sources were estimated for the Little River Basin. Commercial fertilizer and livestock-waste applications on row crops are a principal source of nutrients for most of the Little River Basin. Sources of nutrients in the urban areas of the basin mainly are from effluent discharge from wastewater-treatment facilities and fertilizer applications to lawns and golf courses.

Scientific Investigations Report↗