USGS Science⌕ Search

SEARCH · USGS Science

Results for “Challenge”

Search indexed USGS publications on groundwater, aquifers, geologic maps, mineral resources and earthquakes. Explore source records by subject and place.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 1,225 records · Page 68Linked to original sources
USGS2017

Simultaneous estimation of diet composition and calibration coefficients with fatty acid signature data

Knowledge of animal diets provides essential insights into their life history and ecology, although diet estimation is challenging and remains an active area of research. Quantitative fatty acid signature analysis (QFASA) has become a popular method of estimating diet composition, especially for marine species. A primary assumption of QFASA is that constants called calibration coefficients, which account for the differential metabolism of individual fatty acids, are known. In practice, however, calibration coefficients are not known, but rather have been estimated in feeding trials with captive animals of a limited number of model species. The impossibility of verifying the accuracy of feeding trial derived calibration coefficients to estimate the diets of wild animals is a foundational problem with QFASA that has generated considerable criticism. We present a new model that allows simultaneous estimation of diet composition and calibration coefficients based only on fatty acid signature samples from wild predators and potential prey. Our model performed almost flawlessly in four tests with constructed examples, estimating both diet proportions and calibration coefficients with essentially no error. We also applied the model to data from Chukchi Sea polar bears, obtaining diet estimates that were more diverse than estimates conditioned on feeding trial calibration coefficients. Our model avoids bias in diet estimates caused by conditioning on inaccurate calibration coefficients, invalidates the primary criticism of QFASA, eliminates the need to conduct feeding trials solely for diet estimation, and consequently expands the utility of fatty acid data to investigate aspects of ecology linked to animal diets.

Ecology and Evolution↗
USGS2017

Restricted gene flow between resident Oncorhynchus mykiss and an admixed population of anadromous steelhead

The species Oncorhynchus mykiss is characterized by a complex life history that presents a significant challenge for population monitoring and conservation management. Many factors contribute to genetic variation in O. mykiss populations, including sympatry among migratory phenotypes, habitat heterogeneity, hatchery introgression, and immigration (stray) rates. The relative influences of these and other factors are contingent on characteristics of the local environment. The Rock Creek subbasin in the middle Columbia River has no history of hatchery supplementation and no dams or artificial barriers. Limited intervention and minimal management have led to a dearth of information regarding the genetic distinctiveness of the extant O. mykiss population in Rock Creek and its tributaries. We used 192 SNP markers and collections sampled over a 5‐year period to evaluate the temporal and spatial genetic structures of O. mykiss between upper and lower watersheds of the Rock Creek subbasin. We investigated potential limits to gene flow within the lower watershed where the stream is fragmented by seasonally dry stretches of streambed, and between upper and lower watershed regions. We found minor genetic differentiation within the lower watershed occupied by anadromous steelhead ( F ST = 0.004), and evidence that immigrant influences were prevalent and ubiquitous. Populations in the upper watershed above partial natural barriers were highly distinct ( F ST = 0.093) and minimally impacted by apparent introgression. Genetic structure between watersheds paralleled differences in local demographics (e.g., variation in size), migratory restrictions, and habitat discontinuity. The evidence of restricted gene flow between putative remnant resident populations in the upper watershed and the admixed anadromous population in the lower watershed has implications for local steelhead productivity and regional conservation.

Washington↗
USGS2017

Ad hoc instrumentation methods in ecological studies produce highly biased temperature measurements

In light of global climate change, ecological studies increasingly address effects of temperature on organisms and ecosystems. To measure air temperature at biologically relevant scales in the field, ecologists often use small, portable temperature sensors. Sensors must be shielded from solar radiation to provide accurate temperature measurements, but our review of 18 years of ecological literature indicates that shielding practices vary across studies (when reported at all), and that ecologists often invent and construct ad hoc radiation shields without testing their efficacy. We performed two field experiments to examine the accuracy of temperature observations from three commonly used portable data loggers (HOBO Pro, HOBO Pendant, and iButton hygrochron) housed in manufactured Gill shields or ad hoc, custom‐fabricated shields constructed from everyday materials such as plastic cups. We installed this sensor array (five replicates of 11 sensor‐shield combinations) at weather stations located in open and forested sites. HOBO Pro sensors with Gill shields were the most accurate devices, with a mean absolute error of 0.2°C relative to weather stations at each site. Error in ad hoc shield treatments ranged from 0.8 to 3.0°C, with the largest errors at the open site. We then deployed one replicate of each sensor‐shield combination at five sites that varied in the amount of urban impervious surface cover, which presents a further shielding challenge. Bias in sensors paired with ad hoc shields increased by up to 0.7°C for every 10% increase in impervious surface. Our results indicate that, due to variable shielding practices, the ecological literature likely includes highly biased temperature data that cannot be compared directly across studies. If left unaddressed, these errors will hinder efforts to predict biological responses to climate change. We call for greater standardization in how temperature data are recorded in the field, handled in analyses, and reported in publications.

Ecology and Evolution↗
USGS2017

Temporal constraints on the potential role of fry odors as cues of past reproductive success for spawning lake trout

Deciding where to reproduce is a major challenge for most animals. Many select habitats based upon cues of successful reproduction by conspecifics, such as the presence of offspring from past reproductive events. For example, some fishes select spawning habitat following odors released by juveniles whose rearing habitat overlaps with spawning habitat. However, juveniles may emigrate before adults begin to search for spawning habitat; hence, the efficacy of juvenile cues could be constrained by degradation or dissipation rates. In lake trout ( Salvelinus namaycush ), odors deposited by the previous year's offspring have been hypothesized to guide adults to spawning reefs. However, in most extant populations, lake trout fry emigrate from spawning reefs during the spring and adults spawn during the fall. Therefore, we postulated that the role of fry odors in guiding habitat selection might be constrained by the time between fry emigration and adult spawning. Time course chemical, physiological, and behavioral assays indicated that the odors deposited by fry likely degrade or dissipate before adults select spawning habitats. Furthermore, fry feces did not attract wild lake trout to constructed spawning reefs in Lake Huron. Taken together, our results indicate fry odors are unlikely to act as cues for lake trout searching for spawning reefs in populations whose juveniles emigrate before the spawning season, and underscore the importance of environmental constraints on social cues.

Ecology and Evolution↗
USGS2018

Infrared heater system for warming tropical forest understory plants and soils

The response of tropical forests to global warming is one of the largest uncertainties in predicting the future carbon balance of Earth. To determine the likely effects of elevated temperatures on tropical forest understory plants and soils, as well as other ecosystems, an infrared (IR) heater system was developed to provide in situ warming for the Tropical Responses to Altered Climate Experiment (TRACE) in the Luquillo Experimental Forest in Puerto Rico. Three replicate heated 4-m- diameter plots were warmed to maintain a 4°C increase in understory vegetation compared to three unheated control plots, as sensed by IR thermometers. The equipment was larger than any used previously and was subjected to challenges different from those of many temperate ecosystem warming systems, including frequent power surges and outages, high humidity, heavy rains, hurricanes, saturated clayey soils, and steep slopes. The system was able to maintain the target 4.0°C increase in hourly average vegetation temperatures to within ± 0.1°C. The vegetation was heterogeneous and on a 21° slope, which decreased uniformity of the warming treatment on the plots; yet, the green leaves were fairly uniformly warmed, and there was little difference among 0–10 cm depth soil temperatures at the plot centers, edges, and midway between. Soil temperatures at the 40–50 cm depth increased about 3°C compared to the controls after a month of warming. As expected, the soil in the heated plots dried faster than that of the control plots, but the average soil moisture remained adequate for the plants. The TRACE heating system produced an adequately uniform warming precisely controlled down to at least 50-cm soil depth, thereby creating a treatment that allows for assessing mechanistic responses of tropical plants and soil to warming, with applicability to other ecosystems. No physical obstacles to scaling the approach to taller vegetation (i.e., trees) and larger plots were observed.

Puerto Rico↗
USGS2018

Improving geographically extensive acoustic survey designs for modeling species occurrence with imperfect detection and misidentification

Acoustic recording units (ARUs) enable geographically extensive surveys of sensitive and elusive species. However, a hidden cost of using ARU data for modeling species occupancy is that prohibitive amounts of human verification may be required to correct species identifications made from automated software. Bat acoustic studies exemplify this challenge because large volumes of echolocation calls could be recorded and automatically classified to species. The standard occupancy model requires aggregating verified recordings to construct confirmed detection/non‐detection datasets. The multistep data processing workflow is not necessarily transparent nor consistent among studies. We share a workflow diagramming strategy that could provide coherency among practitioners. A false‐positive occupancy model is explored that accounts for misclassification errors and enables potential reduction in the number of confirmed detections. Simulations informed by real data were used to evaluate how much confirmation effort could be reduced without sacrificing site occupancy and detection error estimator bias and precision. We found even under a 50% reduction in total confirmation effort, estimator properties were reasonable for our assumed survey design, species‐specific parameter values, and desired precision. For transferability, a fully documented r package, OCacoustic, for implementing a false‐positive occupancy model is provided. Practitioners can apply OCacoustic to optimize their own study design (required sample sizes, number of visits, and confirmation scenarios) for properly implementing a false‐positive occupancy model with bat or other wildlife acoustic data. Additionally, our work highlights the importance of clearly defining research objectives and data processing strategies at the outset to align the study design with desired statistical inferences.

Ecology and Evolution↗
USGS2018

Changing environmental gradients over forty years alter ecomorphological variation in Guadalupe Bass Micropterus treculii throughout a river basin

Understanding the degree of intraspecific variation within and among populations is a key aspect of predicting the capacity of a species to respond to anthropogenic disturbances. However, intraspecific variation is usually assessed at either limited temporal, but broad spatial scales or vice versa, which can make assessing changes in response to long-term disturbances challenging. We evaluated the relationship between the longitudinal gradient of changing flow regimes and land use/land cover patterns since 1980 and morphological variation of Guadalupe Bass Micropterus treculii throughout the Colorado River Basin of central Texas. The Colorado River Basin in Texas has experienced major alterations to the hydrologic regime due to changing land- and water-use patterns. Historical collections of Guadalupe Bass prior to rapid human-induced change present the unique opportunity to study the response of populations to varying environmental conditions through space and time. Morphological differentiation of Guadalupe Bass associated with temporal changes in flow regimes and land use/land cover patterns suggests that they are exhibiting intraspecific trait variability, with contemporary individuals showing increased body depth, in response to environmental alteration through time (specifically related to an increase in herbaceous land cover, maximum flows, and the number of low pulses and high pulses). Additionally, individuals from tributaries with increased hydrologic alteration associated with urbanization or agricultural withdrawals tended to have a greater distance between the anal and caudal fin. These results reveal trait variation that may help to buffer populations under conditions of increased urbanization and sprawl, human population growth, and climate risk, all of which impose novel selective pressures, especially on endemic species like Guadalupe Bass. Our results contribute an understanding of the adaptability and capacity of an endemic population to respond to expected future changes based on demographic or climatic projection.

Texas↗
USGS2018

Estimating distemper virus dynamics among wolves and grizzly bears using serology and Bayesian state‐space models

Many parasites infect multiple hosts, but estimating the transmission across host species remains a key challenge in disease ecology. We investigated the within and across host species dynamics of canine distemper virus (CDV) in grizzly bears ( Ursus arctos ) and wolves ( Canis lupus ) of the Greater Yellowstone Ecosystem (GYE). We hypothesized that grizzly bears may be more likely to be exposed to CDV during outbreaks in the wolf population because grizzly bears often displace wolves while scavenging carcasses. We used serological data collected from 1984 to 2014 in conjunction with Bayesian state‐space models to infer the temporal dynamics of CDV. These models accounted for the unknown timing of pathogen exposure, and we assessed how different testing thresholds and the potential for testing errors affected our conclusions. We identified three main CDV outbreaks (1999, 2005, and 2008) in wolves, which were more obvious when we used higher diagnostic thresholds to qualify as seropositive. There was some evidence for increased exposure rates in grizzly bears in 2005, but the magnitude of the wolf effect on bear exposures was poorly estimated and depended upon our prior distributions. Grizzly bears were exposed to CDV prior to wolf reintroduction and during time periods outside of known wolf outbreaks, thus wolves are only one of several potential routes for grizzly bear exposures. Our modeling approach accounts for several of the shortcomings of serological data and is applicable to many wildlife disease systems, but is most informative when testing intervals are short. CDV circulates in a wide range of carnivore species, but it remains unclear whether the disease persists locally within the GYE carnivore community or is periodically reintroduced from distant regions with larger host populations.

Ecology and Evolution↗
USGS2018

Genetic analyses reveal cryptic introgression in secretive marsh bird populations

Hybridization is common in bird populations but can be challenging for management, especially if one of the two parent species is of greater conservation concern than the other. King rails (Rallus elegans) and clapper rails (R. crepitans) are two marsh bird species with similar morphologies, behaviors, and overlapping distributions. The two species are found along a salinity gradient with the king rail in freshwater marshes and the clapper in estuarine marshes. However, this separation is not absolute; they are occasionally sympatric, and there are reports of interbreeding. In Virginia, USA, both king and clapper rails are identified by the state as Species of Greater Conservation Need, although clappers are thought to be more abundant and king rails have a higher priority ranking. We used a mitochondrial DNA marker and 13 diagnostic nuclear single nucleotide polymorphisms (SNPs) to identify species, classify the degree of introgression, and explore the evolutionary history of introgression in two putative clapper rail focal populations along a salinity gradient in coastal Virginia. Genetic analyses revealed cryptic introgression with site-specific rates of admixture. We identified a pattern of introgression where clapper rail alleles predominate in brackish marshes. These results suggest clapper rails may be displacing king rails in Virginia coastal waterways, most likely as a result of ecological selection. As introgression can result in various outcomes from outbreeding depression to local adaptation, continued monitoring of these populations would allow further exploration of hybrid fitness and inform conservation management.

Georgia, New Jersey, North Carolina, Rhode Island,↗
USGS2019

Disease‐structured N‐mixture models: A practical guide to model disease dynamics using count data

Obtaining inferences on disease dynamics (e.g., host population size, pathogen prevalence, transmission rate, host survival probability) typically requires marking and tracking individuals over time. While multistate mark–recapture models can produce high‐quality inference, these techniques are difficult to employ at large spatial and long temporal scales or in small remnant host populations decimated by virulent pathogens, where low recapture rates may preclude the use of mark–recapture techniques. Recently developed N ‐mixture models offer a statistical framework for estimating wildlife disease dynamics from count data. N ‐mixture models are a type of state‐space model in which observation error is attributed to failing to detect some individuals when they are present (i.e., false negatives). The analysis approach uses repeated surveys of sites over a period of population closure to estimate detection probability. We review the challenges of modeling disease dynamics and describe how N ‐mixture models can be used to estimate common metrics, including pathogen prevalence, transmission, and recovery rates while accounting for imperfect host and pathogen detection. We also offer a perspective on future research directions at the intersection of quantitative and disease ecology, including the estimation of false positives in pathogen presence, spatially explicit disease‐structured N ‐mixture models, and the integration of other data types with count data to inform disease dynamics. Managers rely on accurate and precise estimates of disease dynamics to develop strategies to mitigate pathogen impacts on host populations. At a time when pathogens pose one of the greatest threats to biodiversity, statistical methods that lead to robust inferences on host populations are critically needed for rapid, rather than incremental, assessments of the impacts of emerging infectious diseases.

Ecology and Evolution↗
USGS2019

Coast to coast: High genomic connectivity in North American scoters

Dispersal shapes demographic processes and therefore is fundamental to understanding biological, ecological, and evolutionary processes acting within populations. However, assessing population connectivity in scoters ( Melanitta sp.) is challenging as these species have large spatial distributions that span remote landscapes, have varying nesting distributions (disjunct vs. continuous), exhibit unknown levels of dispersal, and vary in the timing of the formation of pair bonds (winter vs. fall/spring migration) that may influence the distribution of genetic diversity. Here, we used double‐digest restriction‐associated DNA sequence (ddRAD) and microsatellite genotype data to assess population structure within the three North American species of scoter (black scoter, M. americana ; white‐winged scoter, M. deglandi ; surf scoter, M. perspicillata ), and between their European congeners (common scoter, M. nigra ; velvet scoter, M. fusca ). We uncovered no or weak genomic structure (ddRAD Φ ST < 0.019; microsatellite F ST < 0.004) within North America but high levels of structure among European congeners (ddRAD Φ ST > 0.155, microsatellite F ST > 0.086). The pattern of limited genomic structure within North America is shared with other sea duck species and is often attributed to male‐biased dispersal. Further, migratory tendencies (east vs. west) of female surf and white‐winged scoters in central Canada are known to vary across years, providing additional opportunities for intracontinental dispersal and a mechanism for the maintenance of genomic connectivity across North America. In contrast, the black scoter had relatively elevated levels of divergence between Alaska and Atlantic sites and a second genetic cluster found in Alaska at ddRAD loci was concordant with its disjunct breeding distribution suggestive of a dispersal barrier (behavioral or physical). Although scoter populations appear to be connected through a dispersal network, a small percentage (<4%) of ddRAD loci had elevated divergence which may be useful in linking areas (nesting, molting, staging, and wintering) throughout the annual cycle.

North America↗
USGS2019

Are polar bear habitat resource selection functions developed from 1985-1996 data still useful?

1. Greenhouse gas-induced warming in the Arctic has caused declines in sea ice extent and changed its composition, raising concerns by all circumpolar nations for polar bear conservation. 2. Negative impacts have been observed in three well-studied polar bear subpopulations. Most subpopulations, however, receive little or no direct monitoring, hence, resource selection functions (RSF) may provide a useful proxy of polar bear distributions. However, the efficacy of RSFs constructed from past data, i.e., reference RSFs, may be degraded under contemporary conditions, especially in a rapidly changing environment. 3. We assessed published Arctic-wide reference RSFs using tracking data from adult female polar bears captured in the Beaufort Sea. We compared telemetry-derived seasonal distributions of polar bears to RSF-defined optimal sea ice habitat during the period of RSF model development, 1985–1995, and two subsequent periods with diminished sea ice: 1996–2006 and 2007–2016. From these comparisons, we assessed the applicability of the reference RSFs for contemporary polar bear conservation. 4. In the two decades following the 1985–1995 reference period, use and availability of optimal habitat by polar bears declined during the ice melt, ice minimum and ice growth seasons. During the ice maximum season (i.e., winter), polar bears used the best habitat available, which changed relatively little across the three decades of study. During the ice melt, ice minimum and ice growth seasons, optimal habitat in areas used by polar bears decreased and was displaced north and east of the Alaska Beaufort Sea coast. As optimal habitat diminished in these seasons, polar bears expanded their range and occupied greater areas of sub-optimal habitat. 5. Synthesis and applications: Sea ice declines due to climate change continue to challenge polar bears and their conservation. The distribution of Southern Beaufort Sea polar bears remained similar during the ice maximum season, so the reference RSFs developed from data collected >20 years ago continue to accurately model their winter distribution. In contrast, reference RSFs for the ice transitional and minimum seasons showed diminished predictive efficacy but were useful in revealing that contemporary polar bears have been increasingly forced to use sub-optimal habitats during those seasons.

Ecology and Evolution↗
USGS2013

Modeling ecological minimum requirements for distribution of greater sage-grouse leks: implications for population connectivity across their western range, U.S.A.

Greater sage-grouse Centrocercus urophasianus (Bonaparte) currently occupy approximately half of their historical distribution across western North America. Sage-grouse are a candidate for endangered species listing due to habitat and population fragmentation coupled with inadequate regulation to control development in critical areas. Conservation planning would benefit from accurate maps delineating required habitats and movement corridors. However, developing a species distribution model that incorporates the diversity of habitats used by sage-grouse across their widespread distribution has statistical and logistical challenges. We first identified the ecological minimums limiting sage-grouse, mapped similarity to the multivariate set of minimums, and delineated connectivity across a 920,000 km 2 region. We partitioned a Mahalanobis D 2 model of habitat use into k separate additive components each representing independent combinations of species–habitat relationships to identify the ecological minimums required by sage-grouse. We constructed the model from abiotic, land cover, and anthropogenic variables measured at leks (breeding) and surrounding areas within 5 km. We evaluated model partitions using a random subset of leks and historic locations and selected D 2 (k = 10) for mapping a habitat similarity index (HSI). Finally, we delineated connectivity by converting the mapped HSI to a resistance surface. Sage-grouse required sagebrush-dominated landscapes containing minimal levels of human land use. Sage-grouse used relatively arid regions characterized by shallow slopes, even terrain, and low amounts of forest, grassland, and agriculture in the surrounding landscape. Most populations were interconnected although several outlying populations were isolated because of distance or lack of habitat corridors for exchange. Land management agencies currently are revising land-use plans and designating critical habitat to conserve sage-grouse and avoid endangered species listing. Our results identifying attributes important for delineating habitats or modeling connectivity will facilitate conservation and management of landscapes important for supporting current and future sage-grouse populations.

Ecology and Evolution↗
USGS2020

Applications of deep convolutional neural networks to predict length, circumference, and weight from mostly dewatered images of fish

Simple biometric data of fish aid fishery management tasks such as monitoring the structure of fish populations and regulating recreational harvest. While these data are foundational to fishery research and management, the collection of length and weight data through physical handling of the fish is challenging as it is time consuming for personnel and can be stressful for the fish. Recent advances in imaging technology and machine learning now offer alternatives for capturing biometric data. To investigate the potential of deep convolutional neural networks to predict biometric data, several regressors were trained and evaluated on data stemming from the FishL™ Recognition System and manual measurements of length, girth, and weight. The dataset consisted of 694 fish from 22 different species common to Laurentian Great Lakes. Even with such a diverse dataset and variety of presentations by the fish, the regressors proved to be robust and achieved competitive mean percent errors in the range of 5.5 to 7.6% for length and girth on an evaluation dataset. Potential applications of this work could increase the efficiency and accuracy of routine survey work by fishery professionals and provide a means for longer‐term automated collection of fish biometric data.

Illinois, Michigan, Ohio↗
USGS2024

Predator-specific mortality of sage-grouse nests based on predator DNA on eggshells

Greater sage-grouse (hereafter sage-grouse; Centrocercus urophasianus ) populations have declined across their range. Increased nest predation as a result of anthropogenic land use is one mechanism proposed to explain these declines. However, sage-grouse contend with a diverse suite of nest predators that vary in functional traits (e.g., search tactics or hunting mode) and abundance. Consequently, generalizing about factors influencing nest fate is challenging. Identifying the explicit predator species responsible for nest predation events is, therefore, critical to understanding causal mechanisms linking land use to patterns of sage-grouse nest success. Cattle grazing is often assumed to adversely affect sage-grouse recruitment by reducing grass height (and hence cover), thereby facilitating nest detection by predators. However, recent evidence found little support for the hypothesized effect of grazing on nest fate at the pasture scale. Rather, nest success appears to be similar on pastures grazed at varying intensities. One possible explanation for the lack of observed effect involves a localized response by one or more nest predators. The presence of cattle may cause a temporary reduction in predator density and/or use within a pasture (the cattle avoidance hypothesis). The cattle avoidance hypothesis predicts a decreased probability of at least one sage-grouse nest predator predating sage-grouse nests in pastures with livestock relative to pastures without livestock present during the nesting season. To test the cattle avoidance hypothesis, we collected predator DNA from eggshells from predated nests and used genetic methods to identify the sage-grouse nest predator(s) responsible for the predation event. We evaluated the influence of habitat and grazing on predator-specific nest predation. We evaluated the efficacy of our genetic method by deploying artificial nests with trail cameras and compared the results of our genetic method to the species captured via trail camera. Our molecular methods identified at least one nest predator captured predating artificial nests via trail camera for 33 of 35 (94%) artificial nests. We detected nest predators via our molecular analysis at 76 of 114 (67%) predated sage-grouse nests. The primary predators detected at sage-grouse nests were coyotes ( Canis latrans ) and corvids ( Corvidea ). Grazing did not influence the probability of nest predation by either coyotes or corvids. Sagebrush canopy cover was negatively associated with the probability a coyote predated a nest, distance to water was positively associated with the probability a corvid predated a nest, and average minimum temperature was negatively associated with the probability that either a coyote or a corvid predated a nest. Our study provides a framework for implementing an effective, non-invasive method for identifying sage-grouse nest predators that can be used to better understand how management actions at local and regional scales may impact an important component of sage-grouse recruitment.

Idaho↗
USGS2025

Balancing monitoring and management in the adaptive management of an invasive species

Efficient allocation of managers' limited resources is necessary to effectively control invasive species, but determining how to allocate effort between monitoring and management over space and time remains a challenge. In an adaptive management context, monitoring data are key for gaining knowledge and iteratively improving management, but monitoring costs money. Community science or other opportunistic monitoring data present an opportunity for managers to gain critical knowledge without a substantial reduction in management funds. We designed a management strategy evaluation to investigate optimal spatial allocation of resources to monitoring and management, while also exploring the potential for community science data to improve decision-making, using adaptive management of invasive flowering rush ( Butomus umbellatus ) in the Columbia River, USA, as a case study. We evaluated management and monitoring alternatives under two invasion conditions, a well-established invasion and an emerging invasion, for both risk-neutral and risk-averse decision makers. Simulations revealed that regardless of invasion condition or managers' risk tolerance, allocating effort outward from the estimated center of invasion ( Epicenter prioritization) resulted in the lowest overall level of infestation at the end of management. This allocation outperformed alternatives in which management occurred in fixed areas ( Linear prioritization) and alternatives that targeted patchily distributed areas with the highest estimated infestation level of the invasive species ( High invasion prioritization). Additionally, management outcomes improved when more resources were allocated toward removal effort than monitoring effort, and the addition of community science data improved outcomes only under certain scenarios. Finally, actions that led to the best outcomes often did not produce the most accurate and precise estimates of parameters describing system function, emphasizing the importance of using value of information principles to guide monitoring. Our adaptive management approach is adaptable to many invasive species management contexts in which ongoing monitoring allows management strategies to be updated over time.

Oregon, Washington↗
USGS2025

Interpreting a sudden population decline in a long-lived species (Malaclemys terrapin rhizophorarum)

Long-term ecological studies are critical for providing insight into population dynamics and detecting population declines, particularly for species of conservation concern. However, spatiotemporal variation and logistical challenges make the identification of sudden population declines difficult. We conducted an in-water capture-mark-recapture study of mangrove diamond-backed terrapins ( Malaclemys terrapin rhizophorarum ) within Big Sable Creek, in Everglades National Park, Florida. We used an 18-year dataset (2001 to 2019) incorporating year, sex, hurricane occurrence, and sampling effort to estimate survival using Cormack–Jolly–Seber (CJS) models in Program Mark. Annual survivorship estimates were high from 2001 to 2003 for both sexes (91%–96%) and variable from 2006 to 2014 (77%–92%). Beginning in 2015, survival estimates exhibited a steeper decline (females: 65%, males 75%), and dropped to below 36% by 2018. Because the driver of this apparent population decline is unknown, we created a population projection matrix and used model-estimated annual survival to simulate annual terrapin population size. We then generated competing scenarios of low survival at various age classes to attempt to reproduce a simulated decline mirroring what we observed from our capture data. A scenario of low adult survival (75%–85%) from 2012 to 2018, possibly in conjunction with no reproduction after 2010, provides estimates of abundance that appear to match simulated annual population size and may indicate that adult emigration/human removal or a drastic drop in recruitment could be responsible for the apparent decline in survival. We explore reasons for this apparent decline and highlight difficulties common to long-term studies that may influence how declines are interpreted.

Florida↗
USGS2025

Development of PCR blocking primers enabling DNA metabarcoding analysis of dietary composition in hematophagous sea lamprey

Conventional dietary assessments are challenging in hematophagous species, particularly in sea lamprey ( Petromyzon marinus ). However, recent technological developments and molecular approaches have provided an attractive alternative through the use of DNA metabarcoding. While DNA metabarcoding has been used for dietary analyses in numerous species, including lampreys, applications of universal primers that detect a diverse set of prey items can be limited by the amplification of predator DNA. In this study, we designed and tested eight blocking primers designed to suppress the amplification of sea lamprey DNA with vertebrate-universal primers targeting the mitochondrial 12S rRNA gene. This approach allowed for the use of a single marker to amplify a taxonomically diverse suite of host species, in contrast to previous studies that used multiple taxon-specific primer pairs (e.g., Salmonidae, Cyprinidae, and Catostomidae). Candidate blocking primers evaluated in this study differed in base pair length, end sequence modification, and purification method. Samples with different sea lamprey-to-host DNA ratios were subjected to multiple detection methods including gel electrophoresis, quantitative PCR, and DNA metabarcoding to assess the ability of each blocking primer to selectively suppress amplification of the sea lamprey 12S gene region. All blocking primers tested performed well and demonstrated high effectiveness, suppressing sea lamprey reads by > 99.9% in mock communities and improving host DNA sequence recovery across various sample types, including wild-caught lamprey. Results show that the blocking primers evaluated can facilitate molecular diet analysis in sea lamprey, allowing the amplification of a taxonomically diverse range of host fish species with universal primers.

Great Lakes↗