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At least 919 records · Page 51Linked to original sources
USGS2019

Drought-mediated extinction of an arid-land amphibian: Insights from a spatially explicit dynamic occupancy model

Understanding how natural and anthropogenic processes affect population dynamics of species with patchy distributions is critical to predicting their responses to environmental changes. Despite considerable evidence that demographic rates and dispersal patterns vary temporally in response to an array of biotic and abiotic processes, few applications of metapopulation theory have sought to explore factors that explain spatio-temporal variation in extinction or colonization rates. To facilitate exploring these factors, we extended a spatially explicit model of metapopulation dynamics to create a framework that requires only binary presence-absence data, makes few assumptions about the dispersal process, and accounts for imperfect detection. We apply this framework to 22 years of biannual survey data for lowland leopard frogs, Lithobates yavapaiensis, an amphibian that inhabits arid stream systems in the southwestern U.S. and northern Mexico. Our results highlight the importance of accounting for factors that govern temporal variation in transition probabilities, as both extinction and colonization rates varied with hydrologic conditions. Specifically, local extinctions were more frequent during drought periods, particularly at sites without reliable surface water. Colonization rates increased when larval and dispersal periods were wetter than normal, which increased the probability that potential emigrants metamorphosed and reached neighboring sites. Extirpation of frogs from one watershed during a period of severe drought demonstrated the influence of site-level features, as frogs persisted only in areas where most sites held water consistently and where the amount of sediment deposited from high-elevation wildfires was low. Application of our model provided novel insights into how climate-related processes affected the distribution and population dynamics of an arid-land amphibian. The approach we describe has application to a wide array of species that inhabit patchy environments, can improve our understanding of factors that govern metapopulation dynamics, and can inform strategies for conservation of imperiled species.

Arizona↗
USGS2021

A more representative community of ecologists

Ecologists play a crucial role in providing solutions to the challenges facing the world. For most of the history of the field, however, the science of ecology has been pursued by white men, and increasingly, by white women. This lack of diversity is untenable today, not only because it is socially unjust, but also because solving environmental problems requires diversity. Ecology as a science is an extremely rewarding and fun career choice for many, but how can the field recruit a more diverse workforce to do this important and gratifying work? Attracting and retaining future ecologists of color is the focus of this Forum. How do young people choose a career in ecology and environmental sciences? For many ecologists, environmental scientists and managers, and future natural resource professionals, an early field experience provides a crucial introduction and gateway. A sojourn at a field station, an extended field trip, or field expedition has introduced many of today’s professionals to their fields, but at the same time, a growing literature documents problematic behavior, discrimination, and other forms of harassment that have been far too frequently reported, and little attention has been given to conscious or implicit exclusion of students from diverse backgrounds. In their lead article, Bowser and Cid, two leading researchers and long-time champions of diversity in ecology, build on experience in long-running programs as well as the literature to diagnose challenges facing diverse youth, and present approaches to encourage, rather than discourage, further engagement. They describe affirmative and creative measures that foster a sense of inclusion and community among young scholars; this sense of belonging and empowerment allows many to advance to studies and careers in ecology and environmental science. In the subsequent six papers, authors explore topics either responding to, or inspired by, the lead paper. They explore alternatives to a field experience as a gateway to a career in ecology or environmental sciences through, for example, data science or the social sciences. Other comment papers describe challenges faced in the next phases of an academic career, barriers faced by specific cultural groups and the approaches, challenges, and outcomes of programs aiming to increase the diversity of the environmental STEM workforce. All responses sound a clarion call for change to hear and value different voices and perspectives to be heard and valued. These include (1) structural and cultural change to our institutions and reward structures; (2) developing and nurturing personal relationships among students and their mentors, within teams and in internships; (3) making entry to ecology inviting and making advancement in ecology free from systemic barriers; and (4) broadening our vision of ecology, and the ways we learn about the world’s ecosystems. The Ecological Society of America, the home for Ecological Applications , is committed to the diversity, equity and inclusion needed to tackle environmental challenges in unity (https://www.esa.org/esablog/2020/09/24/time-for-action-esa-initiates-a-diversity-equity-inclusion-and-justice-deij-task-force/). The world needs all available talent and perspectives to meet environmental challenges today. Ecological Applications has long published occasional papers on the profession of ecology and never ones more important or timely than these. The editorial team is proud to provide an outlet for the voices of our field, in all its current, if inadequate, diversity and honored to host the passionate and committed views of our authors.

Ecological Applications↗
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,↗
USGS2025

Multiple dimensions define thresholds for population resilience of the eastern oyster, Crassostrea virginica

A species' distribution depends on its tolerance to environmental conditions. These conditions are defined by a minimum, maximum, and optimal ranges of single and combined factors. Forays into environmental conditions outside the minimum or maximum tolerance of a species (i.e., thresholds) are predicted to have large effects on a species' population and may help predict population resilience in the face of changing conditions. Here, we explore ecological thresholds for an important fisheries species and ecosystem engineer, Crassostrea virginica (eastern oyster). In coastal Louisiana, extreme freshwater inputs from rivers and precipitation events impact estuarine salinity, which is a key driver of oyster population dynamics. Using daily salinity and monthly oyster abundance monitoring data across Louisiana estuaries, we explore low salinity exposure threshold levels for oysters. Two statistical approaches were applied, with each model highlighting a different operational definition of a threshold: random forest models identified a threshold as an abrupt change in the oyster abundance- salinity relationship, while Bayesian models identified an increased probability of oyster abundance dropping below a critical threshold, defined here as less than 50% of the 5-year mean. All model results indicate oysters in coastal Louisiana experience low salinity exposure thresholds, defined as the number of consecutive summer days of salinity levels less than 5. However, actual number of days and salinity threshold differed by statistical approach, oyster life stage, and estuary highlighting the multiple dimensions defining ecological thresholds. While thresholds are considered important benchmarks to inform management and assess population or ecosystem vulnerability, our results reveal the need to carefully relate threshold definition to management goals and to acknowledge that thresholds may be highly context dependent.

Louisiana↗
USGS2019

Spatially-structured statistical network models for landscape genetics

A basic understanding of how the landscape impedes, or creates resistance to, the dispersal of organisms and hence gene flow is paramount for successful conservation science and management. Spatially structured ecological networks are often used to represent spatial landscape‐genetic relationships, where nodes represent individuals or populations and resistance to movement is represented using non‐binary edge weights. Weights are typically assigned or estimated by the user, rather than observed, and validating such weights is challenging. We provide a synthesis of current methods used to estimate edge weights and an overview of common model types, stressing the advantages and disadvantages of each approach and their ability to model landscape‐genetic data. We further explore a set of spatial‐statistical methods that provide ecologists with alternative approaches for modeling spatially explicit processes that may affect genetic structure. This includes an overview of spatial autoregressive models, with a particular focus on how correlation and partial correlation are used to represent neighborhood structure with the inverse of the covariance matrix (i.e., precision matrix). We then demonstrate how to model resistance by specifying an appropriate statistical model on the nodes, conditioned on the edge weights, through the precision matrix. This integration of network ecology and spatial statistics provides a practical analytical framework for landscape‐genetic studies. The results can be used to make statistical inferences about the relative importance of individual landscape characteristics, such as the vegetative cover, hillslope, or the presence of roads or rivers, on gene flow. In addition, the R code we include allows readers to explore landscape‐genetic structure in their own datasets, which will potentially provide new insights into the evolutionary processes that generated ecological networks, as well as valuable information about the optimal characteristics of conservation corridors.

Ecological Monographs↗
USGS2024

Increasing soil water drought in response to altered precipitation timing across the western United States

Recent trends of rising temperatures and longer droughts between precipitation events are impacting water-limited dryland ecosystems in the western United States. Although ecosystem drought response depends directly on soil moisture, trends in soil moisture (e.g., edaphic drought) remain more poorly explored than precipitation (e.g., meteorological drought), representing an important knowledge gap. Here, we applied the SOILWAT2 ecosystem water balance model to quantify long-term trends of soil moisture and edaphic drought using observed daily weather from 1976 to 2019 at 337 stations across the western United States. We assessed edaphic drought for different plant community types (grass dominated vs. shrub dominated), and explored variations with soil depth and texture. The duration of the longest edaphic drought in a given year increased by 1.5 ± 0.2 days/decade for grassy and 1.7 ± 0.2 days/decade for woody vegetation. Importantly, these trends in edaphic drought were consistent with but greater in magnitude compared with meteorological drought indicating more severe water stress for both plants and ecosystems. The correlation between meteorological drought and edaphic drought was greater under woody vegetation (0.45) compared with grass (0.34) and greater at surface soil depths (0–20 cm; 0.46) compared with the deeper soil (20–100 cm; 0.34). Among soil textures, the correlation between meteorological and edaphic drought was highest on sandy soils and lowest on finer textured silty soils. Using the biogeographic domains (eight western NEON domains), we found that the Pacific Northwest, Pacific Southwest, and Desert Southwest exhibited the strongest increases in edaphic drought through time, but lower correlation between meteorological and edaphic droughts. These findings characterize strong but variable connections between edaphic drought and meteorological drought across the western United States and demonstrate the critical influences of vegetation type, soil depth, and soil properties in mediating the magnitude and spatial distribution of edaphic drought.

western United States↗
USGS2017

Detect and exploit hidden structure in fatty acid signature data

Estimates of predator diet composition are essential to our understanding of their ecology. Although several methods of estimating diet are practiced, methods based on biomarkers have become increasingly common. Quantitative fatty acid signature analysis (QFASA) is a popular method that continues to be refined and extended. Quantitative fatty acid signature analysis is based on differences in the signatures of prey types, often species, which are recognized and designated by investigators. Similarly, predator signatures may be structured by known factors such as sex or age class, and the season or region of sample collection. The recognized structure in signature data inherently influences QFASA results in important and typically beneficial ways. However, predator and prey signatures may contain additional, hidden structure that investigators either choose not to incorporate into an analysis or of which they are unaware, being caused by unknown ecological mechanisms. Hidden structure also influences QFASA results, most often negatively. We developed a new method to explore signature data for hidden structure, called divisive magnetic clustering (DIMAC). Our DIMAC approach is based on the same distance measure used in diet estimation, closely linking methods of data exploration and parameter estimation, and it does not require data transformation or distributional assumptions, as do many multivariate ordination methods in common use. We investigated the potential benefits of the DIMAC method to detect and subsequently exploit hidden structure in signature data using two prey signature libraries with quite different characteristics. We found that the existence of hidden structure in prey signatures can increase the confusion between prey types and thereby reduce the accuracy and precision of QFASA diet estimates. Conversely, the detection and exploitation of hidden structure represent a potential opportunity to improve predator diet estimates and may lead to new insights into the ecology of either predator or prey. The DIMAC algorithm is implemented in the R diet estimation package qfasar.

Ecosphere↗
USGS2019

Developing an expert elicited simulation model to evaluate invasive species and fire management alternatives

Invasive species can alter ecosystem properties and cause state shifts in landscapes. Resource managers charged with maintaining landscapes require tools to understand implications of alternative actions (or inactions) on landscape structure and function. Simulation models can serve as a virtual laboratory to explore these alternatives and their potential impacts on a landscape. To be useful, however, managers need to participate in model development to ensure that model structure can evaluate the response of key resources to plausible actions. Here, we detail development of a state‐and‐transition simulation model (STSM) to evaluate buffelgrass ( Cenchrus ciliaris L. syn Pennisetum ciliare (L.) Link) in Saguaro National Park (SNP), Arizona, USA, through collaboration between managers and researchers. We integrate expert knowledge and research to create and parameterize a stochastic, spatially explicit STSM to evaluate specific management objectives. We also develop a dynamic link between the STSM and a fire behavior model to allow exploration of potential novel processes introduced to the ecosystem by buffelgrass invasion. Our projections show that buffelgrass can be expected to increase on the landscape and that the integration of fire into the model accelerates the projected rate of invasion and increases degradation of resources of management concern. We highlight the benefit of engaging end users in the modeling process so that the model is targeted to evaluate management objectives, in this case retention of saguaro cacti ( Carnegiea gigantea (Engelm.) Britton & Rose) on the landscape. Being able to integrate an external model that can help address the unique characteristics of a problem such as the introduction of fire into the SNP desert ecosystem increases the ability of simulations to address complex ecological and management questions.

Ecosphere↗
USGS2019

Soil characteristics are associated with gradients of big sagebrush canopy structure after disturbance

Reestablishing shrub canopy cover after disturbance in semi-arid ecosystems, such as sagebrush steppe, is essential to provide wildlife habitat and restore ecosystem functioning. While several studies have explored the effects of landscape and climate factors on the success or failure of sagebrush seeding, the influence of soil properties on gradients of shrub canopy structure in successfully seeded areas remains largely unexplored. In this study, we evaluated associations between soil properties and gradients in sagebrush canopy structure in stands that had successfully reestablished after fire and subsequent seeding treatments. Using a dataset collected across the Great Basin, USA, of sagebrush stands that had burned and reestablished between 1986 and 2013, we tested soil depth and texture, soil surface classification, biological soil crusts plus mean historical precipitation, solar heatload, and fire history as modeling variables to explore gradients in sagebrush canopy structure growth in terms of cover, height, and density. Deeper soils were associated with greater sagebrush canopy structure development in terms of plant density and percent cover, coarser textured soils were associated with greater sagebrush cover and density, and more clayey soils were typically associated with greater height. Biological crust presence was also positively associated with enhanced sagebrush canopy growth, but adding more demographically or morphologically explicit descriptions of biocrust communities did not improve explanatory power. Increasing heatload had a negative effect on sagebrush canopy structure growth, and increased mean annual precipitation was only associated with greater sagebrush height. Given that conservation and restoration of the sagebrush steppe ecosystems has become a priority for land managers, the associations we identify between gradients in post-fire sagebrush canopy structure growth and field-identifiable soil characteristics may improve planning of land treatments for sagebrush restoration and the understanding of semi-arid ecosystem functioning and post-disturbance dynamics.

Ecosphere↗
USGS2020

Dynamic Habitat Disturbance and Ecological Resilience (DyHDER): Modeling population responses to habitat condition

Understanding how populations respond to spatially heterogeneous habitat disturbance is as critical to conservation as it is challenging. Here, we present a new, free, and open-source metapopulation model: Dynamic Habitat Disturbance and Ecological Resilience (DyHDER), which incorporates subpopulation habitat condition and connectivity into a population viability analysis framework. Modeling temporally dynamic and spatially explicit habitat disturbance of varying magnitude and duration is accomplished through the use of habitat time-series data and a mechanistic approach to adjusting subpopulation vital rates. Additionally, DyHDER uses a probabilistic dispersal model driven by site-specific habitat suitability, density dependence, and directionally dependent connectivity. In the first application of DyHDER, we explore how fragmentation and projected climate change are predicted to impact a well-studied Bonneville cutthroat trout metapopulation in the Logan River (Utah, USA). The DyHDER model predicts which subpopulations are most susceptible to disturbance, as well as the potential interactions between stressors. Further, the model predicts how populations may be expected to redistribute following disturbance. This information is valuable to conservationists and managers faced with protecting populations of conservation concern across landscapes undergoing changing disturbance regimes. The DyHDER model provides a valuable and generalizable new tool to explore metapopulation resilience to spatially and temporally dynamic stressors for a diverse range of taxa and ecosystems.

Ecosphere↗
USGS2021

Comparing sample bias correction methods for species distribution modeling using virtual species

A key assumption in species distribution modeling (SDM) with presence‐background (PB) methods is that sampling of occurrence localities is unbiased and that any sampling bias is proportional to the background distribution of environmental covariates. This assumption is rarely met when SDM practitioners rely on federated museum records from natural history collections for geo‐located occurrences due to inherent sampling bias found in these collections. We use a simulation approach to explore the effectiveness of three methods developed to account for sampling bias in SDM with PB frameworks. Two of the methods rely on careful filtering of observation data—geographic thinning (G‐Filter) and environmental thinning (E‐Filter)—while a third, FactorBiasOut, creates selection weights for background data to bias locations toward areas where the observation dataset was sampled. While these methods have been assessed previously, evaluation has emphasized spatial predictions of habitat potential. Here, we dig deeper into the effectiveness of these methods by exploring how sampling bias not only affects predictions of habitat potential, but also our understanding of niche characteristics such as which explanatory variables and response curves best represent species–environment relationships. We simulate 100 virtual species ranging from generalist to specialist in their habitat preferences and introduce geographic and environmental bias at three intensity levels to measure the effectiveness of each correction method to (1) predict true probability of occurrence across a study area, (2) recover true species–environment relationships, and (3) identify true explanatory variables. We find that the FactorBiasOut most often showed the greatest improvement in recreating known distributions but did no better at correctly identifying environmental covariates or recreating species–environment relationships than G‐Filter or E‐Filter methods. Narrow niche species are most problematic for biased calibration datasets, such that correction methods can, in some cases, make predictions worse.

Ecosphere↗
USGS2024

Resource availability and heterogeneity affect space use and resource selection of a feral ungulate

Animals adjust their habitat use patterns in response to changes in their physiological needs and environmental conditions. Understanding the mechanisms underlying resource selection and space use across time and space reveals effects of the environment on animals' decisions. We explored the effects of habitat availability and heterogeneity on the seasonal and annual space use and resource selection of two free-roaming feral burro ( Equus asinus ) populations in the United States within distinct climate and habitat conditions: the Sonoran Desert and the Colorado Plateau. As an introduced yet protected species in the United States, understanding burros' interactions with habitat elements is important for their conservation and management, as well as the conservation of sympatric wildlife. We used GPS locations of female burros (72 animals across both study areas) to delineate annual and seasonal ranges and resource selection patterns. We evaluated effects of mean and CV of habitat covariates, including forage, distance to water, and topography, representing availability and heterogeneity of resources, on seasonal and annual range size of burros. Moreover, we explored how burro seasonal and annual resource selection patterns were affected by availability and heterogeneity of resources. In the Sonoran Desert study area, burros had smaller seasonal and annual ranges and constant resource selection patterns across a year, likely due to a freshwater lake in the area, making water a nonlimiting resource. Human presence was the greatest factor affecting range size and resource selection in the Sonoran Desert, where burros selected for areas near roads and human recreation. In the Colorado Plateau study area, where resources were more seasonal, we found larger range sizes and fluctuating resource selection patterns compared to the Sonoran Desert population. Spatial variation in forage, water, and topography significantly affected range size of burros inhabiting the Colorado Plateau study area. Productive habitats with available water support smaller ranges and a more consistent pattern of resource selection. Our results highlight the positive effect of habitat heterogeneity and the negative effect of habitat productivity on range size of animals. Our findings contribute to an improved understanding of habitat requirements for free-roaming burros that currently live under various climate and habitat conditions globally.

Arizona, Utah↗
USGS2025

Ecological scenarios: Embracing ecological uncertainty in an era of global change

Scenarios, or plausible characterizations of the future, can help natural resource stewards plan and act under uncertainty. Current methods for developing scenarios for climate change adaptation planning are often focused on exploring uncertainties in future climate, but new approaches are needed to better represent uncertainties in ecological responses. Scenarios that characterize how ecological changes may unfold in response to climate and describe divergent and surprising ecological outcomes can help natural resource stewards recognize signs of nascent ecological transformation and identify opportunities to intervene. Here, we offer principles and approaches for more fully integrating ecological uncertainties into the development of future scenarios. We provide examples of how specific qualitative and quantitative methods can be used to explore variation in ecological responses to a given climate future. We further highlight opportunities for ecological researchers to generate actionable projections that capture uncertainty in both climatic and ecological change in meaningful and manageable ways to support climate change adaptation decision making.

Nebraska↗
USGS2016

Mid-latitude shrub steppe plant communities: Climate change consequences for soil water resources

In the coming century, climate change is projected to impact precipitation and temperature regimes worldwide, with especially large effects in drylands. We use big sagebrush ecosystems as a model dryland ecosystem to explore the impacts of altered climate on ecohydrology and the implications of those changes for big sagebrush plant communities using output from 10 Global Circulation Models (GCMs) for two representative concentration pathways (RCPs). We ask: 1) What is the magnitude of variability in future temperature and precipitation regimes among GCMs and RCPs for big sagebrush ecosystems and 2) How will altered climate and uncertainty in climate forecasts influence key aspects of big sagebrush water balance? We explored these questions across 1980-2010, 2030-2060, and 2070-2100 to determine how changes in water balance might develop through the 21st century. We assessed ecohydrological variables at 898 sagebrush sites across the western US using a process-based soil water model, SOILWAT to model all components of daily water balance using site-specific vegetation parameters and site-specific soil properties for multiple soil layers. Our modeling approach allowed for changes in vegetation based on climate. Temperature increased across all GCMs and RCPs, while changes in precipitation were more variable across GCMs. Winter and spring precipitation was predicted to increase in the future (7% by 2030-2060, 12% by 2070-2100), resulting in slight increases in soil water potential (SWP) in winter. Despite wetter winter soil conditions, SWP decreased in late spring and summer due to increased evapotranspiration (6% by 2030-2060, 10% by 2070-2100) and groundwater recharge (26% and 30% increase by 2030-2060 and 2070-2100). Thus, despite increased precipitation in the cold season, soils may dry out earlier in the year, resulting in potentially longer drier summer conditions. If winter precipitation cannot offset drier summer conditions in the future, we expect big sagebrush regeneration and survival will be negatively impacted, potentially resulting in shifts in the relative abundance of big sagebrush plant functional groups. Our results also highlight the importance of assessing multiple GCMs to understand the range of climate change outcomes on ecohydrology, which was contingent on the GCM chosen.

Ecology↗
USGS2017

Hydrologic metrics for status-and-trends monitoring in urban and urbanizing watersheds

Local governmental agencies are increasingly undertaking potentially costly “status-and-trends” monitoring to evaluate the effectiveness of stormwater control measures and land-use planning strategies, or to satisfy regulatory requirements. Little guidance is presently available for such efforts, and so we have explored the application, interpretation, and temporal limitations of well-established hydrologic metrics of runoff changes from urbanization, making use of an unusually long-duration, high-quality data set from the Pacific Northwest (USA) with direct applicability to urban and urbanizing watersheds. Three metrics previously identified for their utility in identifying hydrologic conditions with biological importance that respond to watershed urbanization—T Qmean (the fraction of time that flows exceed the mean annual discharge), the Richards-Baker Index (characterizing flashiness relative to the mean discharge), and the annual tally of wet-season day-to-day flow reversals (the total number of days that reverse the prior days’ increasing or decreasing trend)—are all successful in stratifying watersheds across a range of urbanization, as measured by total contributing area of urban development. All metrics respond with statistical significance to multi-decadal trends in urbanization, but none detect trends in watershed-scale urbanization over the course of a single decade. This suggests a minimum period over which dependable trends in hydrologic alteration (or improvement) can be detected with confidence. The metrics also prove less well suited to urbanizing watersheds in a semi-arid climate, with only flow reversals showing a response consistent with prior findings from more humid regions. We also explore the use of stage as a surrogate for discharge in calculating these metrics, recognizing potentially significant agency cost savings in data collection with minimal loss of information. This approach is feasible but cannot be implemented under current data-reporting practices, requiring measurement of water-depth values and preservation of the full precision of the original recorded data. With these caveats, however, hydrologic metrics based on stage should prove as or more useful, at least in the context of status-and-trends monitoring, as those based on subsequent calculations of discharge.

Hydrological Processes↗
USGS2018

Simulation of less‐mobile porosity dynamics in contrasting sediment water interface porous media

Considering heterogeneity in porous media pore size and connectivity is essential to predicting reactive solute transport across interfaces. However, exchange with less‐mobile porosity is rarely considered in surface water/groundwater recharge studies. Previous research indicates that a combination of pore‐fluid sampling and geoelectrical measurements can be used to quantify less‐mobile porosity exchange dynamics using the time‐varying relation between fluid and bulk electrical conductivity. For this study, we use macro‐scale (10 s of cm) advection–dispersion solute transport models linked with electrical conduction in COMSOL Multiphysics to explore less‐mobile porosity dynamics in two different types of observed sediment water interface porous media. Modeled sediment textures contrast from strongly layered streambed deposits to poorly sorted lakebed sands and cobbles. During simulated ionic tracer perturbations, a lag between fluid and bulk electrical conductivity, and the resultant hysteresis, is observed for all simulations indicating differential loading of pore spaces with tracer. Less‐mobile exchange parameters are determined graphically from these tracer time series data without the need for inverse numerical model simulation. In both sediment types, effective less‐mobile porosity exchange parameters are variable in response to changes in flow direction and fluid flux. These observed flow‐dependent effects directly impact local less‐mobile residence times and associated contact time for biogeochemical reaction. The simulations indicate that for the sediment textures explored here, less‐mobile porosity exchange is dominated by variable rates of advection through the domain, rather than diffusion of solute, for typical low‐to‐moderate rate (approximately 3–40 cm/day) hyporheic fluid fluxes. Overall, our model‐based results show that less‐mobile porosity may be expected in a range of natural hyporheic sediments and that changes in flowpath orientation and magnitude will impact less‐mobile exchange parameters. These temporal dynamics can be assessed with the geoelectrical experimental tracer method applied at laboratory and field scales.

Hydrological Processes↗
USGS2021

The timing and magnitude of changes to Hortonian overland flow at the watershed scale during the post-fire recovery process

Extreme hydrologic responses following wildfires can lead to floods and debris flows with costly economic and societal impacts. Process-based hydrologic and geomorphic models used to predict the downstream impacts of wildfire must account for temporal changes in hydrologic parameters related to the generation and subsequent routing of infiltration-excess overland flow across the landscape. However, we lack quantitative relationships showing how parameters change with time-since-burning, particularly at the watershed scale. To assess variations in best-fit hydrologic parameters with time, we used the KINEROS2 hydrological model to explore temporal changes in hillslope saturated hydraulic conductivity ( K sh ) and channel hydraulic roughness ( n c ) following a wildfire in the upper Arroyo Seco watershed (41.5 km 2 ), which burned during the 2009 Station fire in the San Gabriel Mountains, California, USA. This study explored runoff-producing storms between 2008 and 2014 to infer watershed hydraulic properties by calibrating the model to observations at the watershed outlet. Modelling indicates K sh is lowest in the first year following the fire and then increases at an average rate of approximately 4.2 mm/h/year during the first 5 years of recovery. The estimated values for K sh in the first year following the fire are similar to those obtained in previous studies on smaller watersheds (<1.5 km 2 ) following the Station fire, suggesting hydrologic changes detected here can be applied to lower-order watersheds. Hydraulic roughness, n c , was lowest in the first year following the fire, but increased by a factor of 2 after 1 year of recovery. Post-fire observations suggest changes in n c are due to changes in grain roughness and vegetation in channels. These results provide quantitative constraints on the magnitude of fire-induced hydrologic changes following severe wildfires in chaparral-dominated ecosystems as well as the timing of hydrologic recovery.

California↗
USGS2012

Spring onset variations and trends in the continental United States: past and regional assessment using temperature-based indices

Phenological data are simple yet sensitive indicators of climate change impacts on ecosystems, but observations have not been made routinely or extensively enough to evaluate spatial and temporal patterns across most continents, including North America. As an alternative, many studies use weather-based algorithms to simulate specific phenological responses. Spring Indices (SI) are a set of complex phenological models that have been successfully applied to evaluate variations and trends in the onset of spring across the Northern Hemisphere’s temperate regions. To date, SI models have been limited by only producing output in locations where both the plants’ chilling and warmth requirements are met. Here, we develop an extended form of the SI (abbreviated SI-x) that expands their application into the subtropics by ignoring chilling requirements while still retaining the utility and accuracy of the original SI (now abbreviated SI-o). The validity of the new indices is tested, and regional SI anomalies are explored across the data-rich continental United States. SI-x variations from 1900 to 2010 show an abrupt and sustained delay in spring onset of about 4–8 d (around 1958) in parts of the Southeast and southern Great Plains, and a comparable advance of 4–8 d (around 1984) in parts of the northern Great Plains and the West. Atmospheric circulation anomalies, linked to large-scale modes of variability, exert modest but significant roles in the timing of spring onset across the United States on interannual and longer timescales. The SI-x are promising metrics for tracking spring onset variations and trends in mid-latitudes, relating them to relevant ecological, hydrological, and socioeconomic phenomena, and exploring connections between atmospheric drivers and seasonal timing.

International Journal of Climatology↗