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USGS2014

From hybrid swarms to swarms of hybrids

Science has shown that the introgression or hybridization of modern humans ( Homo sapiens ) with Neanderthals up to 40,000 YBP may have led to the swarm of modern humans on earth. However, there is little doubt that modern trade and transportation in support of the humans has continued to introduce additional species, genotypes, and hybrids to every country on the globe. We assessed the utility of species distributions modeling of genotypes to assess the risk of current and future invaders. We evaluated 93 locations of the genus Tamarix for which genetic data were available. Maxent models of habitat suitability showed that the hybrid, T. ramosissima x T. chinensis , was slightly greater than the parent taxa (AUCs > 0.83). General linear models of Africanized honey bees, a hybrid cross of Tanzanian Apis mellifera scutellata and a variety of European honey bee including A. m. ligustica , showed that the Africanized bees (AUC = 0.81) may be displacing European honey bees (AUC > 0.76) over large areas of the southwestern U.S. More important, Maxent modeling of sub-populations (A1 and A26 mitotypes based on mDNA) could be accurately modeled (AUC > 0.9), and they responded differently to environmental drivers. This suggests that rapid evolutionary change may be underway in the Africanized bees, allowing the bees to spread into new areas and extending their total range. Protecting native species and ecosystems may benefit from risk maps of harmful invasive species, hybrids, and genotypes.

Environment and Ecology Research↗

USGS2015

Indicators of climate impacts for forests: Recommendations for the U.S. National Climate Assessment Indicators system

The Third National Climate Assessment (NCA) process for the United States focused in part on developing a system of indicators to communicate key aspects of the physical climate, climate impacts, vulnerabilities, and preparedness to inform decisionmakers and the public. Initially, 13 active teams were formed to recommend indicators in a range of categories, including forest, agriculture, grassland, phenology, mitigation, and physical climate. This publication describes the work of the Forest Indicators Technical Team. We briefly describe the NCA indicator system effort, propose and explain our conceptual model for the forest system, present our methods, and discuss our recommendations. Climate is only one driver of changes in U.S. forests; other drivers include socioeconomic drivers such as population and culture, and other environmental drivers such as nutrients, light, and disturbance. We offer additional details of our work for transparency and to inform an NCA indicator Web portal. We recommend metrics for 11 indicators of climate impacts on forest, spanning the range of important aspects of forest as an ecological type and as a sector. Some indicators can be reported in a Web portal now; others need additional work for reporting in the near future. Indicators such as budburst, which are important to forest but more relevant to other NCA indicator teams, are identified. Potential indicators that need more research are also presented.

Report↗

USGS2012

A novel antibody-based biomarker for chronic algal toxin exposure and sub-acute neurotoxicity

The neurotoxic amino acid, domoic acid (DA), is naturally produced by marine phytoplankton and presents a significant threat to the health of marine mammals, seabirds and humans via transfer of the toxin through the foodweb. In humans, acute exposure causes a neurotoxic illness known as amnesic shellfish poisoning characterized by seizures, memory loss, coma and death. Regular monitoring for high DA levels in edible shellfish tissues has been effective in protecting human consumers from acute DA exposure. However, chronic low-level DA exposure remains a concern, particularly in coastal and tribal communities that subsistence harvest shellfish known to contain low levels of the toxin. Domoic acid exposure via consumption of planktivorous fish also has a profound health impact on California sea lions ( Zalophus californianus ) affecting hundreds of animals yearly. Due to increasing algal toxin exposure threats globally, there is a critical need for reliable diagnostic tests for assessing chronic DA exposure in humans and wildlife. Here we report the discovery of a novel DA-specific antibody response that is a signature of chronic low-level exposure identified initially in a zebrafish exposure model and confirmed in naturally exposed wild sea lions. Additionally, we found that chronic exposure in zebrafish caused increased neurologic sensitivity to DA, revealing that repetitive exposure to DA well below the threshold for acute behavioral toxicity has underlying neurotoxic consequences. The discovery that chronic exposure to low levels of a small, water-soluble single amino acid triggers a detectable antibody response is surprising and has profound implications for the development of diagnostic tests for exposure to other pervasive environmental toxins.

PLoS ONE↗

USGS2009

Planning for an uncertain future - Monitoring, integration, and adaptation

The 6.7 billion human inhabitants of the earth have the ability to drastically alter ecosystems and the populations of species that have taken eons to evolve. By better understanding how our actions affect the environment, we stand a better chance of designing successful strategies to manage ecosystems sustainably. Toward this end, the Third Interagency Conference on Research in the Watersheds (ICRW) was convened in Estes Park, CO, on September 8-11, 2008. The Conference provided a forum to present adaptive management as a practical tool for learning how to manage complex ecosystems more sustainably. Further complexity introduced by spatially variable and continuously changing environmental drivers favors this management approach because of its emphasis on adaptation in response to changing conditions or ineffective actions. For climate change in particular, an adaptive approach can more effectively accommodate the uncertainty in future climate scenarios. Scenarios compiled by the Intergovernmental Panel on Climate Change are built on distinct economic, energy, and societal models. The scenarios predict potential changes in greenhouse gases, temperature, precipitation, and atmospheric aerosols, which would have direct or indirect impacts on the timing, volume, and quality of runoff, vegetation, snowpack, stream temperature, groundwater, thawing permafrost, and icecaps. Through presentations and field trips, researchers and stakeholders described how their findings and issues fit into the adaptive management 'learning by doing' paradigm of Assess > Design > Implement > Monitor > Evaluate > Adjust > Assess.

Scientific Investigations Report↗

USGS1987

Modeling potential impacts of the Garrison Diversion Unit project on Sand Lake and Arrowwood National Wildlife Refuges: a feasibility analysis

The Garrison Diversion Unit (GDU) of the Pick-Sloan Missouri Basin program was authorized in 1965, with the purpose of diverting Missouri River water to the James River for irrigation, municipal and industrial water supply, fish and wildlife habitat, recreation, and flood control. The project was reauthorized in 1986, with the specification that comprehensive studies be conducted to address a variety of issues. One of these ongoing studies addresses potential impacts of GDU construction and operation on lands of the National Wildlife Refuge (NWR) system, including Arrowwood and Sand Lake Refuges (the Refuges) on the James River. A number of concerns at these Refuges have been identified; the primary concerns addressed in this report include increased winter return flows, which would limit control of rough fish; increased turbidity during project construction, which would decrease production of sago pondweed; and increased water level fluctuations in the late spring and early summer, which would destroy the nests of some over-water nesting birds. The facilitated workshop described in this report was conducted February 18-20, 1987, under the joint sponsorship of the U.S. Bureau of Reclamation, the U.S. Fish and Wildlife Service, and the North Dakota Game and Fish Department. The primary objectives of the workshop were to evaluate the feasibility of using simulation modeling techniques to estimate GDU impacts on Arrowwood and Sand Lake Refuges and to suggest enhancements to the James River Refuge monitoring program. The workshop was structured around the formulation of four submodels: a Hydrology and Water Quality submodel to simulate changes in Refuge pool elevations, turnover rates, and water quality parameters (e.g., total dissolved solids, turbidity, dissolved oxygen, nutrients, water temperature, pesticides) due to GDU construction and operation; a Vegetation submodel to simulate concomitant changes in wetland communities (e.g., sago pondweed, wet meadows, deep and shallow marsh); a Fish submodel to estimate changes in abundance or biomass of rough fish (carp, buffalo) and sportfish (northern pike); and a Wildlife submodel to calculate indices of waterfowl abundance or habitat suitability (e.g., for mallards, western grebes, migrating diving ducks, white-faced ibis, egrets, over-water nesters). Submodels considered weekly to monthly changes in pools within a Refuge over a time horizon of 30-50 years. Based on workshop discussions and past experience with impact analysis modeling, a phased modeling approach was recommended for the James River Refuges analysis. The first phase would involve two modeling efforts. The existing Sand Lake hydrology model, and a similar one developed for Arrowwood NWR, would be validated and used to predict changes on pool elevations and winter inflows to each pool for a variety of GDU alternatives. Outputs from simulations would then be evaluated in terms of potential fish and wildlife impacts. For example, the models could generate indices comparing the magnitude and timing of winter inflows for pre- and postproject conditions; fisheries biologists could then use these indices to better quantify their concerns relative to potential changes in the frequency of rough-fish control. The other modeling effort in the first phase would involve developing a sago pondweed growth model to integrate Refuge monitoring data and existing literature and perhaps to address some questions concerning turbidity impacts. A second phase of simulation modeling would be undertaken only if the initial analyses of hydrologic outputs indicated significant potential problems and if monitoring and research projects had clarified some of the biological and physical processes that cannot be modeled reliably at the present time (e.g., resuspension of sediments by carp, immigration and winter mortality of fish, loss of waterfowl nests due to wave action). The second phase would attempt to develop an integrated impact assessment model. In order to address some of the biological and physical processes that presently are not well understood, a number of studies and enhancements to the Refuge monitoring program were suggested. The Hydrology and Water Quality workgroup recommended increasing turbidity and dissolved oxygen sampling, dropping expensive analysis of some trace elements, adding more pesticide analysis (including some biological monitoring), and developing better area-capacity data for the Sand Lake hydrology model. The Vegetation workgroup suggested expanding the number of monitoring stations, monitoring photosynthetically active radiation by depth, and modifying the biomass sampling procedure and schedule. Also suggested were additional analyses of existing Refuge monitoring data and additional field studies concerning sago growth under a variety of environmental conditions and effects of rough fish density on sago. A careful examination of Refuge narrative reports was recommended by the Fish workgroup to characterize conditions that led to various rates of winter-kill. Monitoring enhancement related to a better understanding of fish population dynamics included increasing dissolved oxygen monitoring, continuing present monitoring of fish movement upstream from Jamestown Reservoir into Arrowwood NWR, initiating similar efforts for upstream movement into Sand Lake NWR and downstream movements into both Refuges, and augmenting the present gillnetting program (or replacing it) with sampling for population and age/size structure estimates. The Wildlife workgroup suggested estimating the relative density of mallard nests in over-water and wet meadow nesting areas, estimating the number of western grebe nests lost due to wave action, delineating wet meadows on the Refuge vegetation maps, estimating annual tuber consumption by birds, and monitoring insect/macroinvertebrate abundance. The workgroup also suggested research studies to better understand the relationships between food supplies and the growth and survival of ducklings and young grebes. the workshop discussions also helped identify some suggestions for modifying project features that, if feasible from an engineering and operational standpoint, would reduce impacts on Refuge lands. These suggestions included: designing drains with control structures or small "reregulation" reservoirs to hold winter return flows that might adversely affect rough fish control, spreading construction activities over a number of years to reduce potential impacts of turbidity on sago pondweed in any single year, scheduling construction to occur after the spring sprouting and elongation growth stages to reduce impacts on sago pondweed, and installing "quick acting" control structures at Arrowwood NWR to reduce pool level fluctuations that might destroy nests of some over-water nesting waterfowl.

Report↗

USGS2023

Results of validation exercise for Marine Benthic Index

Marine benthic invertebrates (benthos) are key components of the Puget Sound ecosystem. Because of their direct association living in, and sometimes consuming, sediments, benthos can be valuable sentinels of ecosystem health. Therefore, indicators of benthic invertebrate community health can serve as direct measures of sediment and water quality. In 2021, the Puget Sound Partnership funded development of a Marine Benthic Index . The Marine Benthic Index thus developed uses a novel approach that accounts for habitat preferences of the benthic invertebrate species. This report describes the design and results of the exercise conducted to validate the Marine Benthic Index . The goals of the validation exercise were to determine (a) how well the Marine Benthic Index matches more standard ways of assessing community health and (b) how finely it is possible to distinguish between levels of disturbance. A controlled experiment was devised in which simulated benthic communities were generated to correspond to predetermined levels of disturbance, and experts in benthic ecology determined which communities reflected the more-disturbed conditions. In this way, the index was directly compared to traditional methods of assessing benthic communities. The results provide strong evidence that the “latent disturbance” model used to derive the Marine Benthic Index is identifying effects that benthic experts recognize as disturbance. Not only did the model agree with the experts overall, but also the probability of agreement strongly increased with increasing difference in disturbance level. The validation exercise results indicate that the Marine Benthic Index is a reliable method of determining disturbance without the necessity of assuming a priori knowledge of the disturbance. Furthermore, the numerical approach embodied in the Marine Benthic Index has the advantage of being able to find patterns beyond the capability of individual experts to know the effects of human disturbances for all species under all environmental conditions.

Washington↗

USGS2021

Modeling watershed carbon dynamics as affected by land cover change and soil erosion

Process-based ecosystem carbon cycle models typically incorporate vegetation growth, vegetation mortality, and soil respiration as well as the biotic and environmental drivers that influence these variables. However, few spatially explicit process models can efficiently incorporate the influence of land cover change and carbon lateral movement at regional scales or high spatial resolution. This study uses the Land Use and Carbon Scenario Simulator (LUCAS) to demonstrate the development of a fast ecosystem model that not only considers the basic carbon cycle but also incorporates the impact of land cover change, soil erosion, and soil deposition. As input to the LUCAS modeling framework, we used the integrated biosphere simulator (IBIS) to simulate a non-spatial reference carbon cycling scenario without considering land cover change for the Nisqually River watershed in the northwestern United States. We then used the Land Change Monitoring, Assessment, and Projection (LCMAP) remotely sensed 30-m sequential land cover data to generate annual land change history for the Nisqually River area from 1985 to 2017 and used the Unit Stream Powered Erosion and Deposition model (USPED) to estimate annual soil carbon lateral movement. Finally, we combined the annual carbon outputs from IBIS, the land change history from LCMAP, and the soil erosion and deposition from USPED within the LUCAS simulation framework. Results showed that from 1985 to 2017, along with the dynamic land cover changes, total ecosystem biomass carbon increased from 11.4 to 18.6 TgC, mainly due to forest growth. Total ecosystem soil carbon declined from 31.7 to 29.7 TgC, but the overall loss in soil carbon was not uniform across land cover types. Forestland (forest sector) and grassland lost carbon, while wetland, developed land and agricultural land gained carbon. Forest, grassland, and developed land lost 0.0553 TgC during the study period (1.73 Gg of C per year; 1 Gg = 0.001 Tg) from erosion, while wetland gained 0.0071 TgC (0.22 Gg C per year) from deposition. Agricultural land was neutral in terms of soil erosion.

Washington↗

USGS2018

Surrounding land cover types as predictors of palustrine wetland vegetation quality in conterminous USA

The loss of wetland habitats and their often-unique biological communities is a major environmental concern. We examined vegetation data obtained from 380 wetlands sampled in a statistical survey of wetlands in the USA. Our goal was to identify which surrounding land cover types best predict two indices of vegetation quality in wetlands at the regional scale. We considered palustrine wetlands in four regions (Coastal Plains, North Central East, Interior Plains, and West) in which the dominant vegetation was emergent, forested, or scrub-shrub. For each wetland, we calculated weighted proportions of eight land cover types surrounding the area in which vegetation was assessed, in four zones radiating from the edge of the assessment area to 2 km. Using Akaike's Information Criterion, we determined the best 1-, 2- and 3-predictor models of the two indices, using the weighted proportions of the land cover types as potential predictors. Mean values of the two indices were generally higher in the North Central East and Coastal Plains than the other regions for forested and emergent wetlands. In nearly all cases, the best predictors of the indices were not the dominant surrounding land cover types. Overall, proportions of forest (positive effect) and agriculture (negative effect) surrounding the assessment area were the best predictors of the two indices. One or both of these variables were included as predictors in 65 of the 72 models supported by the data. Wetlands surrounding the assessment area had a positive effect on the indices, and ranked third (33%) among the predictors included in supported models. Development had a negative effect on the indices and was included in only 28% of supported models. These results can be used to develop regional management plans for wetlands, such as creating forest buffers around wetlands, or to conserve zones between wetlands to increase habitat connectivity.

Science of the Total Environment↗

USGS2015

FORUM: Effective management of ecological resilience – are we there yet?

Ecological resilience is developing into a credible paradigm for policy development and environmental management for preserving natural capital in a rapidly changing world. However, resilience emerges from complex interactions, limiting the translation of theory into practice. Main limitations include the following: (i) difficulty in quantification and detection of changes in ecological resilience, (ii) a lack of empirical evidence to support preventative or proactive management and (iii) difficulties in managing processes operating across socio-ecological systems that vary in space and time. We highlight recent research with the potential to address these limitations including new and/or improved indicators of resilience and tools to assess scale as a driver of resilience. Synthesis and applications . Effective resilience-based management must be adaptive in nature. To support this, we propose an operational model using resilience-based iterative management actions operating across scales.

Journal of Applied Ecology↗

USGS2018

Maps showing predicted probabilities for selected dissolved oxygen and dissolved manganese threshold events in depth zones used by the domestic and public drinking water supply wells, Central Valley, California

The purpose of the prediction grids for selected redox constituents—dissolved oxygen and dissolved manganese—are intended to provide an understanding of groundwater-quality conditions at the domestic and public-supply drinking water depths. The chemical quality of groundwater and the fate of many contaminants is influenced by redox processes in all aquifers, and understanding the redox conditions horizontally and vertically is critical in evaluating groundwater quality. The redox condition of groundwater—whether oxic (oxygen present) or anoxic (oxygen absent)—strongly influences the oxidation state of a chemical in groundwater. The anoxic dissolved oxygen thresholds of <0.5 milligram per liter (mg/L), <1.0 mg/L, and <2.0 mg/L were selected to apply broadly to regional groundwater-quality investigations. Although the presence of dissolved manganese in groundwater indicates strongly reducing (anoxic) groundwater conditions, it is also considered a “nuisance” constituent in drinking water, making drinking water undesirable with respect to taste, staining, or scaling. Three dissolved manganese thresholds, <50 micrograms per liter (µg/L), <150 µg/L, and <300 µg/L, were selected to create predicted probabilities of exceedances in depth zones used by domestic and public-supply water wells. The 50 µg/L event threshold represents the secondary maximum contaminant level (SMCL) benchmark for manganese (U.S. Environmental Protection Agency, 2017; California Division of Drinking Water, 2014), whereas the 300 µg/L event threshold represents the U.S. Geological Survey (USGS) health-based screening level (HBSL) benchmark, used to put measured concentrations of drinking-water contaminants into a human-health context (Toccalino and others, 2014). The 150 µg/L event threshold represents one-half the USGS HBSL. The resultant dissolved oxygen and dissolved manganese prediction grids may be of interest to water-resource managers, water-quality researchers, and groundwater modelers concerned with the occurrence of natural and anthropogenic contaminants related to anoxic conditions. Prediction grids for selected redox constituents and thresholds were created by the USGS National Water-Quality Assessment (NAWQA) modeling and mapping team.

California↗

USGS2016

Integrating local pastoral knowledge, participatory mapping, and species distribution modeling for risk assessment of invasive rubber vine ( Cryptostegia grandiflora ) in Ethiopia’s Afar region

The threats posed by invasive plants span ecosystems and economies worldwide. Local knowledge of biological invasions has proven beneficial for invasive species research, but to date no work has integrated this knowledge with species distribution modeling for invasion risk assessments. In this study, we integrated pastoral knowledge with Maxent modeling to assess the suitable habitat and potential impacts of invasive Cryptostegia grandiflora Robx. Ex R.Br. (rubber vine) in Ethiopia’s Afar region. We conducted focus groups with seven villages across the Amibara and Awash-Fentale districts. Pastoral knowledge revealed the growing threat of rubber vine, which to date has received limited attention in Ethiopia, and whose presence in Afar was previously unknown to our team. Rubber vine occurrence points were collected in the field with pastoralists and processed in Maxent with MODIS-derived vegetation indices, topographic data, and anthropogenic variables. We tested model fit using a jackknife procedure and validated the final model with an independent occurrence data set collected through participatory mapping activities with pastoralists. A Multivariate Environmental Similarity Surface analysis revealed areas with novel environmental conditions for future targeted surveys. Model performance was evaluated using area under the receiver-operating characteristic curve (AUC) and showed good fit across the jackknife models (average AUC = 0.80) and the final model (test AUC = 0.96). Our results reveal the growing threat rubber vine poses to Afar, with suitable habitat extending downstream of its current known location in the middle Awash River basin. Local pastoral knowledge provided important context for its rapid expansion due to acute changes in seasonality and habitat alteration, in addition to threats posed to numerous endemic tree species that provide critical provisioning ecosystem services. This work demonstrates the utility of integrating local ecological knowledge with species distribution modeling for early detection and targeted surveying of recently established invasive species.

Ecology and Society↗

USGS2018

Leveraging big data towards functionally-based, catchment scale restoration prioritization

The persistence of freshwater degradation has necessitated the growth of an expansive stream and wetland restoration industry, yet restoration prioritization at broad spatial extents is still limited and ad-hoc restoration prevails. The River Basin Restoration Prioritization tool has been developed to incorporate vetted, distributed data models into a catchment scale restoration prioritization framework. Catchment baseline condition and potential improvement with restoration activity is calculated for all National Hydrography Dataset stream reaches and catchments in North Carolina and compared to other catchments within the river subbasin to assess where restoration efforts may best be focused. Hydrologic, water quality, and aquatic habitat quality conditions are assessed with peak flood flow, nitrogen and phosphorus loading, and aquatic species distribution models. The modular nature of the tool leaves ample opportunity for future incorporation of novel and improved datasets to better represent the holistic health of a watershed, and the nature of the datasets used herein allow this framework to be applied at much broader scales than North Carolina.

Environmental Management↗

USGS2000

Long-term impacts of the Exxon Valdez oil spill on sea otters, assessed through age-dependent mortality patterns

We use age distributions of sea otters ( Enhydra lutris ) found dead on beaches of western Prince William Sound, Alaska, between 1976 and 1998 in conjunction with time-varying demographic models to test for lingering effects from the 1989 Exxon Valdez oil spill. Our results show that sea otters in this area had decreased survival rates in the years following the spill and that the effects of the spill on annual survival increased rather than dissipated for older animals. Otters born after the 1989 spill were affected less than those alive in March 1989, but do show continuing negative effects through 1998. Population-wide effects of the spill appear to have slowly dissipated through time, due largely to the loss of cohorts alive during the spill. Our results demonstrate that the difficult-to-detect long-term impacts of environmental disasters may still be highly significant and can be rigorously analyzed by using a combination of population data, modeling techniques, and statistical analyses.

Proceedings of the National Academy of Sciences of↗

USGS2021

Functional connectivity in a continuously distributed, migratory species as revealed by landscape genomics

Maintaining functional connectivity is critical for the long-term conservation of wildlife populations. Landscape genomics provides an opportunity to assess long-term functional connectivity by relating environmental variables to spatial patterns of genomic variation resulting from generations of movement, dispersal and mating behaviors. Identifying landscape features associated with gene flow at large geographic scales for highly mobile species is becoming increasingly possible due to more accessible genomic approaches, improved analytical methods and enhanced computational power. We characterized the genetic structure and diversity of migratory mule deer Odocoileus hemionus using 4051 single nucleotide polymorphisms in 406 individuals sampled across multiple habitats throughout Wyoming, USA. We then identified environmental variables associated with genomic variation within genetic groups and statewide using a stepwise approach to first evaluate nonlinear relationships of landscape resistance with genetic distances and then use mixed-effects modeling to choose top landscape genomic models. We identified three admixed genetic groups of mule deer and found that environmental variables associated with gene flow varied among genetic groups, revealing scale-dependent and regional variation in functional connectivity. At the statewide scale, more gene flow occurred in areas with low elevation and mixed habitat. In the southern genetic group, more gene flow occurred in areas with low elevation. In the northern genetic group, more gene flow occurred in grassland and forest habitats, while highways and energy infrastructure reduced gene flow. In the western genetic group, the null model of isolation by distance best represented genetic patterns. Overall, our findings highlight the role of different seasonal ranges on mule deer genetic connectivity, and show that anthropogenic features hinder connectivity. This study demonstrates the value of combining a large, genome-wide marker set with recent advances in landscape genomics to evaluate functional connectivity in a wide-ranging migratory species.

Wyoming↗

USGS2018

Burn severity controls on postfire Araucaria‐Nothofagus regeneration in the Andean Cordillera

Aim The aim of the study was to investigate postfire regeneration patterns of Araucaria‐Nothofagus forests on the west slope of the Andes; to evaluate the relationship between remotely sensed burn severity and forest mortality; and to assess controls of burn severity on forest response at local spatio‐temporal scales. Location Araucanía region in the western Andean Range of south‐central Chile where fire occurred during the 2001–2002 season. Methods Sampling of prefire stand structure and postfire vegetation response was performed along a burn severity gradient a decade after the fire. We evaluated the relationship between field‐measured tree mortality and satellite‐derived burn severity using a generalized linear model. We fit zero‐inflated mixture models to regeneration data of each genus to assess the importance of abiotic variables, stand characteristics, and biotic interactions. Results The relative version of the delta Normalized Burn Ratio explained 85% of the variability in canopy mortality. Nearly 12,000 hectares burned; the majority at high severity (67%). Regeneration densities of both genera were lower at higher levels of burn severity and higher with greater total basal area (live, dead, and down trees). The relative effect size of burn severity on regeneration was nearly twice as large for Nothofagus , which suggests information legacies of Araucaria have cascading effects on postdisturbance material legacies. Main conclusions Araucaria‐Nothofagus mortality from wildfire can be readily mapped using satellite‐derived burn severity. Although environmental site characteristics and biotic interactions mediate regeneration, basal area, and burn severity are the main mechanisms controlling regeneration. Forest refugia and postfire regeneration are vulnerable to recurrent fire. Therefore, we expect future fire (either increased severity or frequency), driven by landscape level changes, as a potential mechanism that can reduce local resilience of these forests as initial postfire material legacies (e.g., refugia and regeneration) are removed from the landscape. Our findings highlight an approach to quantify important attributes of forest disturbance and refugia, and identify areas for monitoring postdisturbance regeneration as the forests throughout south‐central Chile and Argentina face a multitude of potential change agents.

Journal of Biogeography↗

USGS2022

Evaluation of the Bushy Park Reservoir three-dimensional hydrodynamic and water-quality model, South Carolina, 2012–15

The Bushy Park Reservoir is a relatively shallow impoundment in southeastern South Carolina. The reservoir, located under a semi-tropical climate, is the principal water supply for the city of Charleston, South Carolina, and the surrounding areas including the Bushy Park Industrial Complex. Although there was an adequate supply of freshwater in the reservoir in 2022, water-quality concerns are present over taste-and-odor and saltwater-intrusion issues. From 2013 to 2015, the U.S. Geological Survey (USGS), in cooperation with the Charleston Water System, engaged in a multi-year study of the hydrology and hydrodynamics of Bushy Park Reservoir to better understand factors affecting water-quality conditions in the reservoir. As part of this study, Charleston Water System worked with Tetra Tech, Inc., a consulting and engineering firm, to develop a Bushy Park Reservoir hydrodynamic and water-quality modeling framework, built upon earlier efforts by both Tetra Tech and the U.S. Army Corps of Engineers. At the completion of the new modeling framework, the USGS was requested to evaluate the calibrated hydrodynamic and water-quality model. The Bushy Park Reservoir Environmental Fluid Dynamics Code (EFDC) model was calibrated for the time period from January 1, 2012, to December 31, 2015. The general modeling approach for the newly revised modeling framework, as briefly detailed in this report, was developed with EFDC. The EFDC is a grid-based modeling package that can simulate three-dimensional flow, transport, and water quality in surface-water systems. This report evaluated the capacity of Tetra Tech’s Bushy Park EFDC model to simulate water discharge, water circulation, surface elevations, temperature, salinity, and other water-quality parameters. The USGS model review focused specifically on the following criteria: (1) determine if the model, with additional effort, could be developed into an adequate planning tool for Bushy Park Reservoir; (2) assess the capacity of the model to specifically address water-quality issues in the reservoir related to taste-and-odor and saltwater intrusions; and, (3) evaluate three preliminary water-management scenarios related to reduced water withdrawals in the reservoir and the effect on saltwater intrusion. Overall, the model was able to simulate discharge, flow velocity, and water-surface elevations with generally good agreement between the simulated and measured values. Specifically, the model was able to demonstrate good agreement for discharge at two USGS continuous discharge locations (USGS station 02172002; USGS station 02172040), with Wilmott index of agreements of 0.86 and 0.75, respectively. A total of seven USGS streamgages, located on the West Branch of the Cooper River, Durham Canal, and the Cooper River, were available for water-surface elevations, with index of agreements ranging from 0.74 to 0.99. However, model-simulated water-surface elevation ranges were appreciably high (compared to measured ranges) for two locations near Pinopolis Dam, farthest upstream on the West Branch of the Cooper River. This result may indicate that too much simulated tidal energy propagated through the model domain. For water temperature, 16 calibration stations were available for at least part of the 4-year simulation. The index of agreement range for temperature comparisons was from 0.95 to 1.00, indicating excellent agreement between the measured and simulated results. One of the primary future applications for the Bushy Park Reservoir EFDC model is to determine the extent of saltwater intrusions. A wide range in the salinity prediction quality was simulated with the model. The prediction quality ranged from an index of agreement of 0.15 at Cooper River approximately 2.75 miles southeast of the Tee, South Carolina, to 0.92 at West Branch Cooper River near Moncks Corner, South Carolina. Although the model did not accurately simulate some of the larger salinity deviations resulting during individual hydrologic events, the seasonal salinity trends were adequately simulated with the model during the study period (2012–15). Therefore, it may be difficult to simulate extreme hydrologic events, such as during large storms, where high salinity water is exchanged with Bushy Park Reservoir. There was agreement in model simulation with the measured data either on the quantitative index of agreement values or qualitative agreement in the seasonal salinity data trends. For water quality, the index of agreement values were generally low for total nitrogen, ammonia, nitrate, total Kjeldahl nitrogen, total phosphorus, and orthophosphate. Although general trends were adequately simulated at specific stations, particularly for Bushy Park Reservoir, the model-simulated fit was low across all the constituents described above with index of agreements usually below 0.50. A limitation for simulating nutrient concentrations across the model domain was the lack of characterization for the constituents directly entering Bushy Park Reservoir, or the lack of data directly attributed to the boundary condition (for example, the Cooper River). The other two calibrated water-quality constituents (besides the nutrients mentioned above) were dissolved oxygen and chlorophyll a . Dissolved oxygen varied from index of agreement values from 0.58 to 0.94 for 11 stations, generally indicating agreement with the available measured data. Chlorophyll a , calibrated for seven stations, had a wider range from 0.11 to 0.74 for the index of agreement. With the current modeling framework, taste-and-odor events, related to cyanobacterial blooms, cannot be directly simulated. However, indirect estimates of cyanobacteria concentrations may be obtained by using the chlorophyll a model outputs, which represent total phytoplankton biomass, and the phytoplankton biovolume data by group (diatoms, green algae, cyanobacteria and others) collected from 2012 to 2015. For the Bushy Park Reservoir modeling framework to be used directly for taste-and-odor issues, cyanobacteria must be simulated and calibrated based on observations of cyanobacteria biomass concentrations. In addition to the cyanobacteria sampling conducted within the reservoir between 2012 and 2015, the new model calibration would also require new algae biomass data-collection efforts to characterize the external sources of cyanobacteria entering the Bushy Park Reservoir from tributaries, as well as the internal cycling, production, and decay of cyanobacteria in the hydrologic system. Further improvements to the EFDC model would include expanding the collection of boundary condition datasets, such as water-quality monitoring to determine improved nutrient loads into the model domain. Along with improved water-quality monitoring for the major boundary conditions, continuous discharge, for both Foster Creek and the Back River, would further constrain the flow balance and the loads into Bushy Park Reservoir. In addition to better boundary-condition characterization, it is important to better characterize possible shortcomings specifically to the model domain, such as the grid resolution, bathymetry, and numerical hydrodynamic errors. Further consideration of the model may involve a sensitivity analysis to determine if errors in the simulation outputs, such as discharge, water-surface elevations, and salinity, were more likely caused by poor boundary condition characterization or, specifically, the model setup. Three model scenarios were run with the revised Bushy Park Reservoir model: (1) reduced withdrawals from one of the large intake-discharge locations for Bushy Park Reservoir, the Williams Station; (2) elevated (above background levels) ocean water level causing saltwater intrusion from the ocean through Durham Canal into Bushy Park Reservoir; and (3) overtopping of the Back River Dam at the southernmost end of Bushy Park Reservoir. For the reduced withdrawals scenarios, the largest shift in flow resulted near the Williams Station intake, with the next largest flow change at the southern end of Bushy Park Reservoir, and a net increase in flow out of the Bushy Park Reservoir to the Cooper River by way of the Durham Canal. The effect resulting from scenario 3 on water quality and salinity was small, with larger increases for dissolved oxygen than other constituents at several monitoring stations. For the two scenarios related to saltwater intrusion (including dam overtopping), the changes in salinity generally were found to dissipate in the following 2 weeks and generally back to baseline salinity conditions within 3 months. This result did vary depending on the severity of the storm or length of the dam overtopping event.

South Carolina↗

USGS2010

Simulation of streamflow in the McTier Creek watershed, South Carolina

The McTier Creek watershed is located in the Sand Hills ecoregion of South Carolina and is a small catchment within the Edisto River Basin. Two watershed hydrology models were applied to the McTier Creek watershed as part of a larger scientific investigation to expand the understanding of relations among hydrologic, geochemical, and ecological processes that affect fish-tissue mercury concentrations within the Edisto River Basin. The two models are the topography-based hydrological model (TOPMODEL) and the grid-based mercury model (GBMM). TOPMODEL uses the variable-source area concept for simulating streamflow, and GBMM uses a spatially explicit modified curve-number approach for simulating streamflow. The hydrologic output from TOPMODEL can be used explicitly to simulate the transport of mercury in separate applications, whereas the hydrology output from GBMM is used implicitly in the simulation of mercury fate and transport in GBMM. The modeling efforts were a collaboration between the U.S. Geological Survey and the U.S. Environmental Protection Agency, National Exposure Research Laboratory. Calibrations of TOPMODEL and GBMM were done independently while using the same meteorological data and the same period of record of observed data. Two U.S. Geological Survey streamflow-gaging stations were available for comparison of observed daily mean flow with simulated daily mean flow-station 02172300, McTier Creek near Monetta, South Carolina, and station 02172305, McTier Creek near New Holland, South Carolina. The period of record at the Monetta gage covers a broad range of hydrologic conditions, including a drought and a significant wet period. Calibrating the models under these extreme conditions along with the normal flow conditions included in the record enhances the robustness of the two models. Several quantitative assessments of the goodness of fit between model simulations and the observed daily mean flows were done. These included the Nash-Sutcliffe coefficient of model-fit efficiency index, Pearson's correlation coefficient, the root mean square error, the bias, and the mean absolute error. In addition, a number of graphical tools were used to assess how well the models captured the characteristics of the observed data at the Monetta and New Holland streamflow-gaging stations. The graphical tools included temporal plots of simulated and observed daily mean flows, flow-duration curves, single-mass curves, and various residual plots. The results indicated that TOPMODEL and GBMM generally produced simulations that reasonably capture the quantity, variability, and timing of the observed streamflow. For the periods modeled, the total volume of simulated daily mean flows as compared to the total volume of the observed daily mean flow from TOPMODEL was within 1 to 5 percent, and the total volume from GBMM was within 1 to 10 percent. A noticeable characteristic of the simulated hydrographs from both models is the complexity of balancing groundwater recession and flow at the streamgage when flows peak and recede rapidly. However, GBMM results indicate that groundwater recession, which affects the receding limb of the hydrograph, was more difficult to estimate with the spatially explicit curve number approach. Although the purpose of this report is not to directly compare both models, given the characteristics of the McTier Creek watershed and the fact that GBMM uses the spatially explicit curve number approach as compared to the variable-source-area concept in TOPMODEL, GBMM was able to capture the flow characteristics reasonably well.

South Carolina↗

USGS2015

Updated numerical model with uncertainty assessment of 1950-56 drought conditions on brackish-water movement within the Edwards aquifer, San Antonio, Texas

In 2010, the U.S. Geological Survey, in cooperation with the San Antonio Water System, began a study to assess the brackish-water movement within the Edwards aquifer (more specifically the potential for brackish-water encroachment into wells near the interface between the freshwater and brackish-water transition zones, referred to in this report as the transition-zone interface) and effects on spring discharge at Comal and San Marcos Springs under drought conditions using a numerical model. The quantitative targets of this study are to predict the effects of higher-than-average groundwater withdrawals from wells and drought-of-record rainfall conditions of 1950–56 on (1) dissolved-solids concentration changes at production wells near the transition-zone interface, (2) total spring discharge at Comal and San Marcos Springs, and (3) the groundwater head (head) at Bexar County index well J-17. The predictions of interest, and the parameters implemented into the model, were evaluated to quantify their uncertainty so the results of the predictions could be presented in terms of a 95-percent credible interval. The model area covers the San Antonio and Barton Springs segments of the Edwards aquifer; the history-matching effort was focused on the San Antonio segment. A previously developed diffuse-flow model of the Edwards aquifer, which forms the basis for the model in this assessment, is primarily based on a conceptualization in which flow in the aquifer is predominately through a network of numerous small fractures and openings. Primary updates to this model include an extension of the active area downdip, a conversion to an 8-layer SEAWAT variable-density flow and transport model to simulate dissolved-solids concentration effects on water density, history matching to 1999–2009 conditions, and parameter estimation in a highly parameterized context using automated methods in PEST (a model-independent Parameter ESTimation code). In addition to the best-fit parameter values derived from history matching, the uncertainty of model parameters was also estimated by using linear uncertainty analysis. Comparison of “prior” (before history matching) and “posterior” (after history matching) variances of parameters indicate that the information within the observation dataset used for history matching informs many parameters. The concentration threshold parameters were well-informed by the observation dataset as their posterior distributions were much narrower than their prior distributions. The transition-zone scaling parameters of hydraulic conductivity, effective porosity, and specific storage were all informed by the observation dataset, as evidenced by the difference between the prior and posterior variances. Saline-zone scaling parameters, alternatively, were not informed by the observation dataset for effective porosity and specific storage. Resulting posterior drier-month, wetter-month, and annual recharge multiplier parameter variances are important to understanding how well recharge is estimated and implemented within the model. The shifts of the posterior distributions left and right indicate that there were zones where less or more water was needed in the model. The widths of the distributions were not decreased substantially, indicating that many of the best-fit recharge parameters are not statistically different from the initial values specified in the history-matching effort. Recharge from rainfall is the driving force behind groundwater flow and heads in the aquifer; therefore, an increase in understanding of this process would benefit model development by potentially decreasing the uncertainty of this parameter. The history-matching effort was most helpful in informing the parameters in the model that control discharge at springs, namely, the spring orifice (drain) altitude and drain conductance parameters for each spring. The uncertainty assessment of the predictive model (a hypothetical recurrence of 1950–56 drought conditions and higher-than-average groundwater withdrawals from wells) provided insights into the potential effects of these conditions on dissolved-solids concentration changes at production wells near the transition-zone interface, discharges at Comal and San Marcos Springs, and heads at Bexar County index well J-17. Results at the 25 production wells near the transition-zone interface indicate that the uncertainty of model input parameters based on expert knowledge yielded an upper bound of the 95-percent credible interval of dissolved-solids concentrations that exceeds the secondary drinking water standards of 1,000 milligrams per liter (mg/L) of the Texas Commission on Environmental Quality (TCEQ) for many wells. However, the history-matching process provided key information to inform prediction-sensitive model parameters and therefore, contributed to a substantial decrease of the upper bound of the 95-percent credible interval to below the secondary drinking water standards. Reductions in dissolved-solids concentration changes were on the order of 400 mg/L to 1,300 mg/L. The reduction in uncertainty in regards to this prediction implies that this prediction of dissolved-solids concentration change can be made with some certainty using this current model and that those parameters that control this prediction are informed by the observation dataset. Even though predictive uncertainty was reduced for this prediction, dissolved-solids concentration changes were still greater than zero, indicating a minimal increase in concentration at these 25 production wells during the 7-year simulation period is likely. However, this minimal concentration increase indicates a small potential for movement of the brackish-water transition zone near these wells during the 7-year simulation period of drought-ofrecord (1950–56) rainfall conditions with higher-than-average groundwater withdrawals by wells. Predictive results of total spring discharge during the 7-year period, as well as head predictions at Bexar County index well J-17, were much different than the dissolved-solids concentration change results at the production wells. These upper bounds are an order of magnitude larger than the actual prediction which implies that (1) the predictions of total spring discharge at Comal and San Marcos Springs and head at Bexar County index well J-17 made with this model are not reliable, and (2) parameters that control these predictions are not informed well by the observation dataset during historymatching, even though the history-matching process yielded parameters to reproduce spring discharges and heads at these locations during the history-matching period. Furthermore, because spring discharges at these two springs and heads at Bexar County index well J-17 represent more of a cumulative effect of upstream conditions over a larger distance (and longer time), many more parameters (with their own uncertainties) are potentially controlling these predictions than the prediction of dissolved-solids concentration change at the prediction wells, and therefore contributing to a large posterior uncertainty.

Texas↗