Geology topics

Brian E. Reichert

Publications and source records attributed to Brian E. Reichert.

35 records · Page 2Linked to original sources

USGS2022

NABat ML: Utilizing deep learning to enable crowdsourced development of automated, scalable solutions for documenting North American bat populations

Bats play crucial ecological roles and provide valuable ecosystem services, yet many populations face serious threats from various ecological disturbances. The North American Bat Monitoring Program (NABat) aims to use its technology infrastructure to assess status and trends of bat populations, while developing innovative and community-driven conservation solutions. Here, we present NABat ML , an automated machine-learning algorithm that improves the scalability and scientific transparency of NABat acoustic monitoring. This model combines signal processing techniques and convolutional neural networks (CNNs) to detect and classify recorded bat echolocation calls. We developed our CNN model with internet-based computing resources (‘cloud environment’), and trained it on >600,000 spectrogram images. We also incorporated species range maps to improve the robustness and accuracy of the model for future ‘unseen’ data. We evaluated model performance using a comprehensive, independent, holdout dataset. NABat ML successfully distinguished 31 classes (30 species and a noise class) with overall weighted-average accuracy and precision rates of 92%, and ≥90% classification accuracy for 19 of the bat species. Using a single cloud-environment computing instance, the entire model training process took <16 h. Synthesis and applications . Our convolutional neural network (CNN)-based model, NABat ML , classifies 30 North American bat species using their recorded echolocation calls with an overall accuracy of 92%. In addition to providing highly accurate species-level classification, NABat ML and its outputs are compatible with Bayesian and other statistical techniques for measuring uncertainty in classification. Our model is open-source and reproducible, enabling future implementations as software on end-user devices and cloud-based web applications. These qualities make NABat ML highly suitable for applications ranging from grassroots community science initiatives to big-data methods developed and implemented by researchers and professional practitioners. We believe the transparency and accessibility of NABat ML will encourage broad-scale participation in bat monitoring, and enable development of innovative solutions needed to conserve North American bat species.

Journal of Applied Ecology↗

USGS2022

Statistical assessment on determining local presence of rare bat species

Surveying cryptic, sparsely distributed taxa using autonomous recording units, although cost-effective, provides imperfect knowledge about species presence. Summertime bat acoustic surveys in North America exemplify the challenges with characterizing sources of uncertainty: observation error, inability to census populations, and natural stochastic variation. Statistical uncertainty, if not considered thoroughly, hampers determining rare species presence accurately and/or estimating rangewide status and trends with suitable precision. Bat acoustic data are processed using an automated workflow in which proprietary or open-source algorithms assign a species label to each recorded high-frequency echolocation sequence. A false-negative occurs, if a species is actually present but not recorded and/or all recordings from the species are of such poor quality that a correct species identity cannot be assigned to any observation. False positives for a focal species are a direct result of the presence and incorrect identification of a recording from another species. We compare four analytical approaches in terms of parameter estimation and their resulting (in)correct decisions regarding species presence or absence using realistic data-generating scenarios for bat acoustic data within a simulation study. The current standard for deciding species presence or absence uses a multinomial likelihood-ratio test p value (maximum likelihood estimate [MLE]-metric) that accounts for known species misidentifications, but not imperfect detection and only returns a binary outcome (evidence of presence or not). We found that the MLE-metric had estimated median correct decisions less than 60% for presence and greater than 85% for absence. Alternatively, a multispecies count detection model was equivalent to or better than the MLE-metric for correct claims of rare species presence or absence using the posterior probability a species was present at a site and, importantly, provided unbiased estimates of relative activity and probability of occurrence, creating opportunities for reducing posterior uncertainty through the inclusion of meaningful covariates. Single-species occupancy models with and without false-positive detections removed were insufficient for determining local presence because of substantially biased occurrence and detection probabilities. We propose solutions to potential barriers for integrating local, short-term and rangewide, long-term acoustic surveys within a cohesive statistical framework that facilitates determining local species presence with uncertainty concurrent with estimating species–environment relationships.

Ecosphere↗

USGS2022

Status and trends of North American bats: Summer occupancy analysis 2010-2019

• We developed an analytical pipeline supported by web-based infrastructure for integrating continental scale bat monitoring data (stationary acoustic, mobile acoustic, and capture records) to estimate summer (May 1–Aug 31) occupancy probabilities and changes in occupancy over time for 12 North American bat species. This serves as one of multiple lines of evidence that inform the status and trends of bat populations. • We analyzed data from a total of 12 bat species (Table 1), 11 of which have tested positive for Pseudogymnoascus destructans (Pd), a fungal pathogen that causes white-nose syndrome (WNS)—a disease that has led to significant rates of mortality for subterranean hibernating bat species in North America. A twelfth species was also selected because of high rates of mortality at wind energy facilities. Additional species were considered but not selected due to data limitations. • We estimated occupancy probabilities for 2010 through 2019 for three species ( Myotis lucifugus , MYLU; Myotis septentrionalis , MYSE; and P erimyotis subflavus , PESU). For an additional nine species, we estimated occupancy probabilities for 2016 through 2019 ( Myotis evotis , MYEV; Myotis grisescens , MYGR; Myotis leibii , MYLE; Myotis thysanodes , MYTH; Myotis volans , MYVO; Myotis yumanensis , MYYU; Eptesicus fuscus , EPFU; Lasionycteris noctivagans , LANO; and Lasiurus cinereus , LACI). • For each species, we provide range-wide occupancy probability predictions (e.g., predicted summer occupancy distribution maps) each year at a spatial resolution of 100 km2 and provide regional estimates of mean occupancy probability aggregated at larger spatial scales (state/province/territory, range-wide). • For each species, we also provide trends over time (average annual change rate and total change rate) in mean occupancy probabilities at multiple spatial scales (state/province/territory, range-wide) and when possible, over multiple timescales (short, medium, long). • Results suggest that over the short-term (2016-2019), two ( Myotis lucifugus and Perimyotis subflavus ) of 12 species have experienced declines in range-wide average occupancy probability with at least 95% certainty. Seven species showed either minor increases or decreases in range-wide average occupancy probability but with less than 95% certainty in both trend indicators. Results over the longer term (eight years and 10 years of sampling) suggest that three hibernating species known to be highly affected by white-nose syndrome ( Myotis lucifugus , Myotis septentrionalis , and Perimyotis subflavus ) have experienced marked declines in range-wide average occupancy probabilities, with severity varying by species and region. Finally, the results for three species ( Eptesicus fuscus , Lasiurus cinereus , Lasionycteris noctivagans ) were inconclusive due to 1) borderline convergence issues in the model fitting procedure which suggests potentially unreliable estimates, 2) failure to reliably distinguish between false positives and true positive detections for ambiguous detections, and 3) largely uninformative covariates for occupancy and detection. • For Myotis lucifugus , Myotis septentrionalis , and Perimyotis subflavus we found meaningful associations in space and time between declining winter populations (likely a result of WNS) and summer occupancy distributions. • The representativeness of sampling data for each species’ status and trend estimates (e.g., state/province/territory) were also evaluated based on the percent of grid cells sampled each year with a goal of understanding the reliability of regional estimates and improving future monitoring efforts. • This work represents the most comprehensive effort to date to model North American bat distributions across their continental ranges. Despite current limitations highlighted in the discussion, the analytical methods and resulting status and trends estimates provide the best available science on summer bat populations across North America and will continue to improve over time as monitoring data sets and analytical methods improve. • Moving forward, our occupancy analyses will continue to improve with submission of more 1) data from currently underrepresented areas (i.e., improved geographic representation), 2) manually-vetted acoustic recordings, 3) capture records, and 4) roost location and count data (summer and winter).

Report↗

USGS2021

The scope and severity of white-nose syndrome on hibernating bats in North America

Assessing the scope and severity of threats is necessary for evaluating impacts on populations to inform conservation planning. Quantitative threat assessment often requires monitoring programs that provide reliable data over relevant spatial and temporal scales, yet such programs can be difficult to justify until there is an apparent stressor. Leveraging efforts of wildlife management agencies to record winter counts of hibernating bats, we collated data for 5 species from over 200 sites across 27 U.S. states and 2 Canadian provinces from 1995 to 2018 to determine the impact of white-nose syndrome (WNS), a deadly disease of hibernating bats. We estimated declines of winter counts of bat colonies at sites where the invasive fungus that causes WNS ( Pseudogymnoascus destructans ) had been detected to assess the threat impact of WNS. Three species undergoing species status assessment by the U.S. Fish and Wildlife Service ( Myotis septentrionalis , Myotis lucifugus , and Perimyotis subflavus ) declined by more than 90%, which warrants classifying the severity of the WNS threat as extreme based on criteria used by NatureServe. The scope of the WNS threat as defined by NatureServe criteria was large (36% of Myotis lucifugus range) to pervasive (79% of Myotis septentrionalis range) for these species. Declines for 2 other species ( Myotis sodalis and Eptesicus fuscus ) were less severe but still qualified as moderate to serious based on NatureServe criteria. Data-sharing across jurisdictions provided a comprehensive evaluation of scope and severity of the threat of WNS and indicated regional differences that can inform response efforts at international, national, and state or provincial jurisdictions. We assessed the threat impact of an emerging infectious disease by uniting monitoring efforts across jurisdictional boundaries and demonstrated the importance of coordinated monitoring programs, such as the North American Bat Monitoring Program (NABat), for data-driven conservation assessments and planning.

Conservation Biology↗

USGS2021

NABat: A top-down, bottom-up solution to collaborative continental-scale monitoring

Collaborative monitoring over broad scales and levels of ecological organization can inform conservation efforts necessary to address the contemporary biodiversity crisis. An important challenge to collaborative monitoring is motivating local engagement with enough buy-in from stakeholders while providing adequate top-down direction for scientific rigor, quality control, and coordination. Collaborative monitoring must reconcile this inherent tension between top-down control and bottom-up engagement. Highly mobile and cryptic taxa, such as bats, present a particularly acute challenge. Given their scale of movement, complex life histories, and rapidly expanding threats, understanding population trends of bats requires coordinated broad-scale collaborative monitoring. The North American Bat Monitoring Program (NABat) reconciles top-down, bottom-up tension with a hierarchical master sample survey design, integrated data analysis, dynamic data curation, regional monitoring hubs, and knowledge delivery through web-based infrastructure. NABat supports collaborative monitoring across spatial and organizational scales and the full annual lifecycle of bats.

Ambio↗

USGS2021

The demographic contributions of connectivity versus local dynamics to population growth of an endangered bird

Conservation and management increasingly focus on connectivity, because connectivity driven by variation in immigration rates across landscapes is thought to be crucial for maintaining local population and metapopulation persistence. Yet, efforts to quantify the relative role of immigration on population growth across the entire range of species and over time have been lacking. We assessed whether immigration limited local and range‐wide population growth of the endangered snail kite Rostrhamus sociabilis in Florida, USA, over 18 years using multi‐state, reverse‐time modelling that accounts for imperfect detection of individuals and unobservable states. Demographic contributions of immigration varied depending on the dynamics and geographic position of the local populations, were scale‐dependent and changed over time. By comparing the relative contributions of immigration versus local demography for periods of significant change in local abundance, we found empirical evidence for a disproportionately large role of immigration in facilitating population growth of a centrally located population—a connectivity ‘hub’. The importance of connectivity changed depending of the spatial scale considered, such that immigration was a more important driver of population growth at small versus large spatial scales. Furthermore, the contribution of immigration was much greater during time periods when local population size was small, emphasizing abundance‐dependent rescue effects. Our findings suggest that efforts aimed at improving local breeding habitat will likely be most effective at increasing snail kite population growth. More broadly, our results provide much needed information on the role of connectivity for population growth, suggesting that connectivity conservation may have the greatest benefits when efforts focus on centrally located habitat patches and small populations. Furthermore, our results highlight that connectivity is highly dynamic over time and that interpreting the effects of connectivity at local scales may not transfer to region‐wide dynamics.

Florida↗

USGS2020

U.S. Geological Survey science in support of the North American Bat Monitoring Program (NABat)

Bats make up one-fifth of all mammalian species worldwide and are found on every continent except Antarctica. They contribute to overall ecosystem health by suppressing pest insects and pollinating plants and spreading seeds. Eight North American bat species are listed as federally endangered or threatened, and more than one-half are of current conservation concern in the United States, Canada, or Mexico. The U.S. Geological Survey (USGS) leads, manages, and coordinates the multinational North American Bat Monitoring Program (NABat) as well as conducts scientific research on bats. USGS and NABat partners help resource managers and policymakers make informed decisions regarding the conservation of bats across North America. USGS science also helps inform decision making with respect to WNS surveillance and bat vulnerability; mitigation of potential impacts of energy development on bats; prelisting conservation efforts for regulatory agencies; and land management practices. Partners are essential to the success of NABat. The data contributed by NABat partners provide baseline knowledge on the distribution and abundance of bats, which is used to evaluate the impacts of the threats to bats across North America. These data are also the foundation for the scientific information used to set conservation priorities and evaluate the effectiveness of management actions.

Fact Sheet↗

USGS2020

Case Study 4: NABat acoustic monitoring allows inferences about bat populations at multiple scales

North American bats face unprecedented risks from continuing and emerging threats including white-nose syndrome, wind energy development, and habitat loss. Many species of bats are thought to be recently experiencing unparalleled population declines unlike any previously observed (O’Shea et al. 2016). The North American Bat Monitoring Program (NABat) was conceived to better understand the true ecological consequences of these large-scale population reductions (Loeb et al. 2015). NABat aims is to improve the state of conservation science for the 47 species of bats shared by Canada, United States, and Mexico. To meet this objective, NABat offers standardize protocols and a unifying sample design facilitating a multi-agency, multinational, collaborative monitoring effort. A key element of NABat is cross-boundary partner coordination and sharing of limited resources for the collection of bat echolocation data. Here we provide three compelling examples of how NABat provides a convenient framework for using acoustic data to assess the potential impacts of current and future threats to North American bats across multiple spatial scales.

Oregon↗

USGS2018

Community for Data Integration fiscal year 2017 funded project report

The U.S. Geological Survey Community for Data Integration annually funds small projects focusing on data integration for interdisciplinary research, innovative data management, and demonstration of new technologies. This report provides a summary of the 11 projects funded in fiscal year 2017, outlining their goals, activities, and outputs.

Open-File Report↗

USGS2018

A guide to processing bat acoustic data for the North American Bat Monitoring Program (NABat)

The North American Bat Monitoring Program (NABat) aims to improve the state of conservation science for all species of bats shared by the United States, Canada, and Mexico. To accomplish this goal, NABat offers guidance and standardized protocols for acoustic monitoring of bats. In this document, “A Guide to Processing Bat Acoustic Data for the North American Bat Monitoring Program (NABat),” we provide general recommendations and specific workflows for the process of identifying bat species from acoustic files recorded using the NABat stationary point and mobile transect acoustic monitoring protocols.

Open-File Report↗

USGS2017

Urbanization may limit impacts of an invasive predator on native mammal diversity

Aim Our understanding of the effects of invasive species on faunal diversity is limited in part because invasions often occur in modified landscapes where other drivers of community diversity can exacerbate or reduce the net impacts of an invader. Furthermore, rigorous assessments of the effects of invasive species on native communities that account for variation in sampling, species-specific detection and occurrence of rare species are lacking. Invasive Burmese pythons ( Python molurus bivittatus ) may be causing declines in medium- to large-sized mammals throughout the Greater Everglades Ecosystem (GEE); however, other factors such as urbanization, habitat changes and drastic alteration in water flow may also be influential in structuring mammal communities. The aim of this study was to gain an understanding of how mammal communities simultaneously facing invasive predators and intensively human-altered landscapes are influenced by these drivers and their interactions. Location Florida, USA. Methods We used data from trail cameras and scat searches with a hierarchical community model that accounts for undetected species to determine the relative influence of introduced Burmese pythons, urbanization, local hydrology, habitat types and interactive effects between pythons and urbanization on mammal species occurrence, site-level species richness, and turnover. Results Python density had significant negative effects on all species except coyotes. Despite these negative effects, occurrence of some generalist species increased significantly near urban areas. At the community level, pythons had the greatest impact on species richness, while turnover was greatest along the urbanization gradient where communities were increasingly similar as distance to urbanization decreased. Main conclusions We found evidence for an antagonistic interaction between pythons and urbanization where the impacts of pythons were reduced near urban development. Python-induced changes to mammal communities may be mediated near urban development, but elsewhere in the GEE, pythons are likely causing a fundamental restructuring of the food web, declines in ecosystem function, and creating complex and unpredictable cascading effects.

Florida↗

USGS2016

Spatio-temporal variation in age structure and abundance of the endangered snail kite: Pooling across regions masks a declining and aging population

While variation in age structure over time and space has long been considered important for population dynamics and conservation, reliable estimates of such spatio-temporal variation in age structure have been elusive for wild vertebrate populations. This limitation has arisen because of problems of imperfect detection, the potential for temporary emigration impacting assessments of age structure, and limited information on age. However, identifying patterns in age structure is important for making reliable predictions of both short- and long-term dynamics of populations of conservation concern. Using a multistate superpopulation estimator, we estimated region-specific abundance and age structure (the proportion of individuals within each age class) of a highly endangered population of snail kites for two separate regions in Florida over 17 years (1997–2013). We find that in the southern region of the snail kite—a region known to be critical for the long-term persistence of the species—the population has declined significantly since 1997, and during this time, it has increasingly become dominated by older snail kites (> 12 years old). In contrast, in the northern region—a region historically thought to serve primarily as drought refugia—the population has increased significantly since 2007 and age structure is more evenly distributed among age classes. Given that snail kites show senescence at approximately 13 years of age, where individuals suffer higher mortality rates and lower breeding rates, these results reveal an alarming trend for the southern region. Our work illustrates the importance of accounting for spatial structure when assessing changes in abundance and age distribution and the need for monitoring of age structure in imperiled species.

Florida↗

USGS2013

Network modularity reveals critical scales for connectivity in ecology and evolution

For nearly a century, biologists have emphasized the profound importance of spatial scale for ecology, evolution and conservation. Nonetheless, objectively identifying critical scales has proven incredibly challenging. Here we extend new techniques from physics and social sciences that estimate modularity on networks to identify critical scales for movement and gene flow in animals. Using four species that vary widely in dispersal ability and include both mark-recapture and population genetic data, we identify significant modularity in three species, two of which cannot be explained by geographic distance alone. Importantly, the inclusion of modularity in connectivity and population viability assessments alters conclusions regarding patch importance to connectivity and suggests higher metapopulation viability than when ignoring this hidden spatial scale. We argue that network modularity reveals critical meso-scales that are probably common in populations, providing a powerful means of identifying fundamental scales for biology and for conservation strategies aimed at recovering imperilled species.

Nature Communications↗

USGS2012

Extreme weather and experience influence reproduction in an endangered bird

Extreme weather events, such as droughts and heat waves, are expected to become more severe and more frequent in the coming years, and understanding their impacts on demographic rates is of increasing interest to both evolutionary ecologists and conservation practitioners. An individual's breeding probability can be a sensitive indicator of the decision to initiate reproductive behavior under varying environmental conditions, has strong fitness consequences, and can be considered the first step in a life history trade-off between allocating resources for breeding activities or self-survival. Using a 14-year time series spanning large variation in climatic conditions and the entirety of a population's breeding range, we estimated the effects of extreme weather conditions (drought) on the state-specific probabilities of breeding and survival of an endangered bird, the Florida Snail Kite ( Rostrhamus sociabilis plumbeus ). Our analysis accounted for uncertainty in breeding status assignment, a common source of uncertainty that is often ignored when states are based on field observations. Breeding probabilities in adult kites (>1 year of age) decreased during droughts, whereas the probability of breeding in young kites (1 year of age) tended to increase. Individuals attempting to breed showed no evidence of reduced future survival. Although population viability analyses of this species and other species often implicitly assume that all adults will attempt to breed, we find that breeding probabilities were significantly <1 for all 13 estimable years considered. Our results suggest that experience is an important factor determining whether or not individuals attempt to breed during harsh environmental conditions and that reproductive effort may be constrained by an individual's quality and/or despotic behavior among individuals attempting to breed.

Florida↗

USGS2011

Social network models predict movement and connectivity in ecological landscapes

Network analysis is on the rise across scientific disciplines because of its ability to reveal complex, and often emergent, patterns and dynamics. Nonetheless, a growing concern in network analysis is the use of limited data for constructing networks. This concern is strikingly relevant to ecology and conservation biology, where network analysis is used to infer connectivity across landscapes. In this context, movement among patches is the crucial parameter for interpreting connectivity but because of the difficulty of collecting reliable movement data, most network analysis proceeds with only indirect information on movement across landscapes rather than using observed movement to construct networks. Statistical models developed for social networks provide promising alternatives for landscape network construction because they can leverage limited movement information to predict linkages. Using two mark-recapture datasets on individual movement and connectivity across landscapes, we test whether commonly used network constructions for interpreting connectivity can predict actual linkages and network structure, and we contrast these approaches to social network models. We find that currently applied network constructions for assessing connectivity consistently, and substantially, overpredict actual connectivity, resulting in considerable overestimation of metapopulation lifetime. Furthermore, social network models provide accurate predictions of network structure, and can do so with remarkably limited data on movement. Social network models offer a flexible and powerful way for not only understanding the factors influencing connectivity but also for providing more reliable estimates of connectivity and metapopulation persistence in the face of limited data.

Proceedings of the National Academy of Sciences of↗

USGS2011

Implications of discontinuous elevation gradients on fragmentation and restoration in patterned wetlands

Large wetlands around the world face the possibility of degradation, not only from complete conversion, but also from subtle changes in their structure and function. While fragmentation and isolation of wetlands within heterogeneous landscapes has received much attention, the disruption of spatial patterns/processes within large wetland systems and the resulting fragmentation of community components are less well documented. A greater understanding of pattern/process relationships and landscape gradients, and what occurs when they are altered, could help avoid undesirable consequences of restoration actions. The objective of this study is to determine the amount of fragmentation of sawgrass ridges due to artificial impoundment of water and how that may be differentially affected by spatial position relative to north and south levees. We also introduce groundbreaking evidence of landscape-level discontinuous elevation gradients within WCA3AS by comparing generalized linear and generalized additive models. These relatively abrupt breaks in elevation may have non-linear effects on hydrology and vegetation communities and would be crucial in restoration considerations. Modeling suggests there are abrupt breaks in elevation as a function of northing ( Y -coordinate). Fragmentation indices indicate that fragmentation is a function of elevation and easting ( X -coordinate), and that fragmentation has increased from 1988-2002. When landscapes change and the changes are compounded by non-linear landscape variables that are described herein, the maintenance processes change with them, creating a degraded feedback loop that alters the system's response to structuring variables and diminishes our ability to predict the effects of restoration projects or climate change. Only when these landscape variables and linkages are clearly defined can we predict the response to potential perturbations and apply the knowledge to other landscape-level wetland systems in need of future restoration.

Florida↗

USGS2010

Interactive effects of senescence and natural disturbance on the annual survival probabilities of snail kites

Individuals in wild populations face risks associated with both intrinsic (i.e. aging) and external (i.e. environmental) sources of mortality. Condition-dependent mortality occurs when there is an interaction between such factors; however, few studies have clearly demonstrated condition-dependent mortality and some have even argued that condition-dependent mortality does not occur in wild avian populations. Using large sample sizes (2084 individuals, 3746 re-sights) of individual-based longitudinal data collected over a 33 year period (1976-2008) on multiple cohorts, we used a capture-mark-recapture framework to model age-dependent survival in the snail kite Rostrhamus sociabilis plumbeus population in Florida. Adding to the growing amount of evidence for actuarial senescence in wild populations, we found evidence of senescent declines in survival probabilities in adult kites. We also tested the hypothesis that older kites experienced condition-dependent mortality during a range-wide drought event (2000-2002). The results provide convincing evidence that the annual survival probability of senescent kites was disproportionately affected by the drought relative to the survival probability of prime-aged adults. To our knowledge, this is the first evidence of condition-dependent mortality to be demonstrated in a wild avian population, a finding which challenges recent conclusions drawn in the literature. Our study suggests that senescence and condition-dependent mortality can affect the demography of wild avian populations. Accounting for these sources of variation may be particularly important to appropriately compute estimates of population growth rate, and probabilities of quasi-extinctions.

Oikos↗