Geology topics

Meryl C. Mims

Publications and source records attributed to Meryl C. Mims.

15 recordsLinked to original sources

USGS2025

Some of these are not like the others: Relative thermal sensitivity among anuran species of the Southeast United States

Estimating how close a species is to its upper thermal limits (i.e., warming tolerance, a thermal sensitivity index) and how that proximity changes across space enables spatially explicit identification of species with increased extinction risk as temperatures increase. Yet, thermal sensitivity is often difficult to calculate because it is the result of many traits. We aimed to synthesize multiple traits into a single estimate of relative terrestrial thermal sensitivity for 13 anuran species in the southeastern United States. We employed models that incorporate traits and microclimate variation to (1) estimate species warming tolerance (the difference between species critical thermal maximum and modeled operative temperature, an estimate of body temperature) and (2) investigate how warming tolerance varied with latitude (whereby latitude represents different temperature regimes and external drivers of thermal sensitivity). We ran mechanistic niche models across a 12° latitudinal gradient and 10 years to estimate individual operative temperature. We calculated the minimum, 25th percentile (hottest quarter), and median daily minimum warming tolerance. Estimates of minimum warming tolerance spanned −5 to 10°C ( Lithobates palustris and Gastrophryne carolinensis respectively) and differed among species. For most species, modeled operative temperatures exceeded species' critical thermal maximum during extreme warm temperatures (i.e., heat waves) in part of their range, and warming tolerance increased with latitude. During heat waves, five species had lower warming tolerance at higher latitudes, and three species' warming tolerance did not change with latitude. We identified species that are approaching their thermal limits in the Southeast and characterized spatial patterns of warming tolerance. Increased temperatures could increase anuran extinction risk, posing an additional challenge for threatened anuran species. Spatial patterns of warming tolerance were not consistent among species in our study, highlighting that patterns identified at higher taxonomic categories could be inconsistent at lower taxonomic categories.

southeastern United States↗

USGS2025

Shared leadership can promote success in collaborative research networks in ecology

1. While collaborative science is becoming the norm in ecology, many ecologists participating in collaborations are less aware of the body of research that studies the processes by which collaborative teams organize and communicate. 2. Here, we discuss how we successfully used a shared leadership model in the Dry Rivers Research Coordination Network. We discuss how this model promote dour success in different stages of the project, using the Tuckman model of team development: forming, storming, norming, performing and adjourning. 3. Shared leadership in the forming phase helped us recruit a diverse membership from different scientific disciplines. In the storming and norming phases, shared leadership was especially useful in ensuring that all voices were heard in establishing group norms that promoted adhesion among and investment by RCN members. Shared leadership in the performing phase was crucial in providing opportunities for early career members to lead projects, and in the adjourning phase we reflected upon our entire collaboration to identify that shared leadership was crucial to our success, generating the thesis for this commentary. 4. It is our hope that others may find this discussion of our experience in implementing a shared leadership model useful in developing their own fruitful collaborations.

Functional Ecology↗

USGS2025

Exposure, sensitivity, or adaptive capacity? Reviewing assessments that use only two of three elements of climate change vulnerability

As climate change accelerates, understanding which species are most vulnerable and why they are vulnerable will be vital to inform conservation action. Climate change vulnerability assessments (CCVAs) are tools to assess species' responses to climate change, detect drivers of vulnerability, and inform conservation planning. CCVAs are commonly composed of three elements: exposure, sensitivity, and adaptive capacity. Incorporating all three elements can be challenging, and including only two of the three elements may be a more feasible approach in many systems. Although two-element CCVA approaches have become more common, their utility and procedures remain poorly documented. We conducted a literature review to explore the scope, methods, and rationale of CCVAs that use a two-element approach to assess vertebrate vulnerability. Despite the potential to expand CCVAs into understudied systems, two-element assessments had similar geographic and taxonomic biases as those previously detected in CCVAs in general. Methods varied, yet we found that variables used in two-element studies could be condensed into standardized categories to enhance comparability. Finally, limitations in data availability and computational resources were common rationales for using a two-element approach. By clarifying the purposes, opportunities, and limitations of two-element assessment, this review can aid in selecting appropriate methods for CCVAs.

Conservation Science and Practice↗

USGS2024

Biogeochemical and community ecology responses to the wetting of non-perennial streams

Transitions between dry and wet hydrologic states are the defining characteristic of non-perennial rivers and streams, which constitute the majority of the global river network. Although past work has focused on stream drying characteristics, there has been less focus on how hydrology, ecology and biogeochemistry respond and interact during stream wetting. Wetting mechanisms are highly variable and can range from dramatic floods and debris flows to gradual saturation by upwelling groundwater. This variation in wetting affects ecological and biogeochemical functions, including nutrient processing, sediment transport and the assembly of biotic communities. Here we synthesize evidence describing the hydrological mechanisms underpinning different types of wetting regimes, the associated biogeochemical and organismal responses, and the potential scientific and management implications for downstream ecosystems. This combined multidisciplinary understanding of wetting dynamics in non-perennial streams will be key to predicting and managing for the effects of climate change on non-perennial ecosystems.

Nature Water↗

USGS2024

Spatial extent drives patterns of relative climate change sensitivity for freshwater fishes of the United States

Assessing the sensitivity of freshwater species to climate change is an essential component of prioritizing conservation efforts for threatened freshwater ecosystems and organisms. Sensitivity to climate change can be systematically evaluated for multiple species using geographic attributes such as range size and climate niche breadth, and using species traits associated with climate change sensitivity. These systematic evaluations produce relative rankings of species sensitivity to aid conservation prioritization and to identify relatively sensitive species that may otherwise be understudied or overlooked. Due in part to biogeographic constraints, species assemblages change across regions and spatial extents; yet, the degree to which spatial factors influence relative rankings of species sensitivity is unclear. The spatial extent of multispecies analyses may alter relative rankings of species climate sensitivity; alternatively, relative climate sensitivity may be conserved among spatial scales, resulting in consistent identification of sensitive species among regions and spatial extents. We investigated how spatial extent influences our understanding of relative climate sensitivity for 137 native freshwater fishes of the United States that were representative of taxonomic, trait, and geographic diversity. Using publicly available occurrence data from the Global Biodiversity Information Facility, we calculated a systematic, geographically derived index of climate change sensitivity for study species at national and regional extents, including within four major hydrologic subregions of the United States. We examined the effects of spatial extent on the relative ranking of climate sensitivity among species, and we explored relationships among climate sensitivity, species traits, and conservation status at regional and national extents. We found that climate sensitivity rankings of species were influenced by spatial extent in some specific instances, but that relative rankings were largely conserved across spatial scales. However, correlations among geographically derived climate sensitivity rankings and species traits associated with climate sensitivity were variable across scales and regions, suggesting that links between geographic rarity and species traits may be scale-dependent in some cases. Finally, we found few associations between climate sensitivity and current conservation status among species. Systematic approaches to quantifying climate sensitivity may offer an opportunity to identify sensitive but overlooked species for pre-listing actions such as monitoring or conservation agreements.

Ecosphere↗

USGS2024

Thermal traits of anurans database for the southeastern United States (TRAD): A database of thermal trait values for 40 anuran species

Thermal traits, or how an animal responds to changing temperatures, impacts species persistence and thus biodiversity. Trait databases, as repositories of consolidated, measured organismal attributes, allow researchers to link study species with specific trait values, enabling comparisons within and among species. Trait databases also help lay the groundwork to build mechanistic linkages between organisms and the environment. However, missing or hidden physiological trait data preclude building mechanistic estimates of climate change vulnerability for many species. Thus, physiologically focused trait databases present an opportunity to consolidate data and enable species-specific or multispecies, mechanistic evaluations of climate change vulnerability. Here, we present TRAD: thermal traits of anurans database for the southeastern United States, a database of thermal trait values related to physiological thermoregulation (critical thermal minima and maxima, preferred temperature), behavioral thermoregulation (activity period, retreat emergence temperature, basking temperature, minimum and maximum foraging temperatures), and body mass for 37 anuran species found within the southeastern United States. In total, TRAD contains 858 reported trait values for 37 of 40 species found in the region from 267 peer-reviewed papers, dissertations, or theses and is easily linked with trait data available in ATraiU, an ecological trait database for anurans in the United States. TRAD contains trait values for multiple life stages and a summarization of interspecific adult trait values. Availability of trait data varied widely among traits and species. Estimates of mass were the most common trait values reported, with values available for 32 species. Behavioral trait values comprised 23% of our database, with activity period available for 34 species. We found the most trait values for Cope's Gray Treefrog ( Dryophytes chrysoscelis ), with at least one trait value for eight traits in the database. Conversely, species in the genus Pseudacris generally had the fewest trait values available. Species with the largest geographic range sizes also had the greatest coverage of data across traits (rho 5 0.75, P , 0.001). TRAD can aid studies of anuran response to changing temperatures, physiological niche space and limitations, and potential drivers of anuran geographic range limits, influencing our understanding of other ecological and evolutionary patterns and processes and enabling multispecies comparisons of potential risk and resilience in the face of climate change.

southeastern United States↗

USGS2023

Mismatch between conservation status and climate change sensitivity leaves some anurans in the United States unprotected

Species vulnerable to climate change face increased extinction risk, but many sensitive species may be overlooked due to limited data and exclusion from vulnerability assessments. Intrinsic sensitivity, or the inherent risk of species to environmental change due to biological factors, can be assessed with widely available data and may address gaps in multispecies vulnerability assessments. Species that exist in few places (geographically rare) and in fewer climates (smaller realized climate niche breadth) have high intrinsic sensitivity to environmental change. Using point occurrences, we systematically evaluated intrinsic sensitivity based on geographic rarity and realized climate niche breadth for 90 species of frogs and toads native to the United States using over 140 000 occurrence records. To compare sensitivity to perceived extinction risk, we compared intrinsic sensitivity to conservation status at state, federal, and international levels. We found no relationship between intrinsic sensitivity and federal or state conservation status, with some intrinsically sensitive species (i.e., those with small areas of occurrence and narrow climate specificity) not listed as at-risk at any level. Intrinsic sensitivity analysis can serve as an early warning system for species that may be currently at-risk and overlooked.

Biological Conservation↗

USGS2022

Simple statistical models can be sufficient for testing hypotheses with population time series data

Time-series data offer wide-ranging opportunities to test hypotheses about the physical and biological factors that influence species abundances. Although sophisticated models have been developed and applied to analyze abundance time series, they require information about species detectability that is often unavailable. We propose that in many cases, simpler models are adequate for testing hypotheses. We consider three relatively simple regression models for time series, using simulated and empirical (fish and mammal) datasets. Model A is a conventional generalized linear model of abundance, model B adds a temporal autoregressive term, and model C uses an estimate of population growth rate as a response variable, with the option of including a term for density dependence. All models can be fit using Bayesian and non-Bayesian methods. Simulation results demonstrated that model C tended to have greater support for long-lived, lower-fecundity organisms (K life-history strategists), while model A, the simplest, tended to be supported for shorter-lived, high-fecundity organisms (r life-history strategists). Analysis of real-world fish and mammal datasets found that models A, B, and C each enjoyed support for at least some species, but sometimes yielded different insights. In particular, model C indicated effects of predictor variables that were not evident in analyses with models A and B. Bayesian and frequentist models yielded similar parameter estimates and performance. We conclude that relatively simple models are useful for testing hypotheses about the factors that influence abundance in time-series data, and can be appropriate choices for datasets that lack the information needed to fit more complicated models. When feasible, we advise fitting datasets with multiple models because they can provide complementary information.

Ecology and Evolution↗

USGS2022

Toward improved prediction of streamflow effects on freshwater fishes

Understanding the effects of hydrology on fish populations is essential to managing for native fish conservation. However, despite decades of research illustrating streamflow influences on fish habitat, reproduction and survival, biologists remain challenged when tasked with predicting how fish populations will respond to changes in flow regimes. This uncertainty stems from insufficient understanding of the context-dependent mechanisms underlying fish responses to, for example, periods of reduced flow or altered frequency of high-flow events. We aim to address this gap by drawing on previous research to hypothesize mechanisms by which low- and high-flows influence fish populations and communities, identifying challenges that stem from data limitations and ecological complexity, and outlining research directions that can advance an empirical basis for prediction. Focusing flow-ecology research on testing and refining mechanistic hypotheses can help narrow management uncertainties and better support species conservation in changing flow regimes.

Fisheries Magazine↗

USGS2021

Pervasive changes in stream intermittency across the United States

Non-perennial streams are widespread, critical to ecosystems and society, and the subject of ongoing policy debate. Prior large-scale research on stream intermittency has been based on long-term averages, generally using annually aggregated data to characterize a highly variable process. As a result, it is not well understood if, how, or why the hydrology of non-perennial streams is changing. Here, we investigate trends and drivers of three intermittency signatures that describe the duration, timing, and dry-down period of stream intermittency across the continental United States (CONUS). Half of gages exhibited a significant trend through time in at least one of the three intermittency signatures, and changes in no-flow duration were most pervasive (41% of gages). Changes in intermittency were substantial for many streams, and 7% of gages exhibited changes in annual no-flow duration exceeding 100 days during the study period. Distinct regional patterns of change were evident, with widespread drying in southern CONUS and wetting in northern CONUS. These patterns are correlated with changes in aridity, though drivers of spatiotemporal variability were diverse across the three intermittency signatures. While the no-flow timing and duration were strongly related to climate, dry-down period was most strongly related to watershed land use and physiography. Our results indicate that non-perennial conditions are increasing in prevalence over much of CONUS and binary classifications of 'perennial' and 'non-perennial' are not an accurate reflection of this change. Water management and policy should reflect the changing nature and diverse drivers of changing intermittency both today and in the future.

Environmental Research Letters↗

USGS2021

Spatial patterns and drivers of nonperennial flow regimes in the contiguous United States

Over half of global rivers and streams lack perennial flow, and understanding the distribution and drivers of their flow regimes is critical for understanding their hydrologic, biogeochemical, and ecological functions. We analyzed nonperennial flow regimes using 540 U.S. Geological Survey watersheds across the contiguous United States from 1979 to 2018. Multivariate analyses revealed regional differences in no-flow fraction, date of first no flow, and duration of the dry-down period, with further divergence between natural and human-altered watersheds. Aridity was a primary driver of no-flow metrics at the continental scale, while unique combinations of climatic, physiographic and anthropogenic drivers emerged at regional scales. Dry-down duration showed stronger associations with nonclimate drivers compared to no-flow fraction and timing. Although the sparse distribution of nonperennial gages limits our understanding of such streams, the watersheds examined here suggest the important role of aridity and land cover change in modulating future stream drying.

contiguous United States↗

USGS2020

Zero or not? Causes and consequences of zero-flow stream gage readings

Streamflow observations can be used to understand, predict, and contextualize hydrologic, ecological, and biogeochemical processes and conditions in streams. Stream gages are point measurements along rivers where streamflow is measured, and are often used to infer upstream watershed‐scale processes. When stream gages read zero, this may indicate that the stream has dried at this location; however, zero‐flow readings can also be caused by a wide range of other factors. Our ability to identify whether or not a zero‐flow gage reading indicates a dry fluvial system has far reaching environmental implications. Incorrect identification and interpretation by the data user can lead to inaccurate hydrologic, ecological, and/or biogeochemical predictions from models and analyses. Here, we describe several causes of zero‐flow gage readings: frozen surface water, flow reversals, instrument error, and natural or human‐driven upstream source losses or bypass flow. For these examples, we discuss the implications of zero‐flow interpretations. We also highlight additional methods for determining flow presence, including direct observations, statistical methods, and hydrologic models, which can be applied to interpret causes of zero‐flow gage readings and implications for reach‐ and watershed‐scale dynamics. Such efforts are necessary to improve our ability to understand and predict surface flow activation, cessation, and connectivity across river networks. Developing this integrated understanding of the wide range of possible meanings of zero‐flows will only attain greater importance in a more variable and changing hydrologic climate.

WIREs Water↗

USGS2019

Simulating demography, genetics, and spatially explicit processes to inform reintroduction of a threatened char

The success of species reintroductions can depend on a combination of environmental, demographic, and genetic factors. Although the importance of these factors in the success of reintroductions is well‐accepted, they are typically evaluated independently, which can miss important interactions. For species that persist in metapopulations, movement through and interaction with the landscape is predicted to be a vital component of persistence. Simulation‐based approaches are a promising technique for evaluating the independent and combined effects of these factors on the outcome of various reintroduction and associated management actions. We report results from a simulation study of bull trout ( Salvelinus confluentus ) reintroduction to three watersheds of the Pend Oreille River system in northeastern Washington State, USA. We used an individual‐based, spatially explicit simulation model to evaluate how reintroduction strategies, life history variation, and riverscape structure (e.g., network topology) interact to influence the demographic and genetic characteristics of reintroduced bull trout populations in three watersheds. Simulation scenarios included a range of initial genetic stocks (informed by empirical bull trout genetic data), variation in migratory tendency and life history, and two landscape connectivity alternatives representing a connected network (isolation‐by‐distance) and a fragmented network (isolation‐by‐barrier, using the known existing barriers). A novel feature of these simulations was the ability to consider the interaction of both demographic and genetic (i.e., demogenetic) factors in riverscapes with implicit asymmetric movement probabilities across the barriers. We found that connectivity (presence or absence of barriers) had the largest effect on demographic and genetic outcomes over 200 yr, with a greater effect than both initial genetic diversity and life history variation. We also identified regions of the study system in which bull trout populations persisted across a wide range of demographic, life history, and environmental connectivity parameters. Finally, we found no evidence that initial neutral genetic diversity influenced genetic diversity and structure after 200 yr; instead, genetic drift due to stray rate and population isolation dominated and erased any initial differences in genetic diversity. Our results highlight the utility of spatially explicit demogenetic approaches in exploring and understanding population dynamics—and their implications for management strategies—in fresh waters.

Washington↗

USGS2014

Are large-scale flow experiments informing the science and management of freshwater ecosystems?

Greater scientific knowledge, changing societal values, and legislative mandates have emphasized the importance of implementing large-scale flow experiments (FEs) downstream of dams. We provide the first global assessment of FEs to evaluate their success in advancing science and informing management decisions. Systematic review of 113 FEs across 20 countries revealed that clear articulation of experimental objectives, while not universally practiced, was crucial for achieving management outcomes and changing dam-operating policies. Furthermore, changes to dam operations were three times less likely when FEs were conducted primarily for scientific purposes. Despite the recognized importance of riverine flow regimes, four-fifths of FEs involved only discrete flow events. Over three-quarters of FEs documented both abiotic and biotic outcomes, but only one-third examined multiple taxonomic responses, thus limiting how FE results can inform holistic dam management. Future FEs will present new opportunities to advance scientifically credible water policies.

Frontiers in Ecology and the Environment↗

USGS2011

Large-scale flow experiments for managing river systems

Experimental manipulations of streamflow have been used globally in recent decades to mitigate the impacts of dam operations on river systems. Rivers are challenging subjects for experimentation, because they are open systems that cannot be isolated from their social context. We identify principles to address the challenges of conducting effective large-scale flow experiments. Flow experiments have both scientific and social value when they help to resolve specific questions about the ecological action of flow with a clear nexus to water policies and decisions. Water managers must integrate new information into operating policies for large-scale experiments to be effective. Modeling and monitoring can be integrated with experiments to analyze long-term ecological responses. Experimental design should include spatially extensive observations and well-defined, repeated treatments. Large-scale flow manipulations are only a part of dam operations that affect river systems. Scientists can ensure that experimental manipulations continue to be a valuable approach for the scientifically based management of river systems.

BioScience↗