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At least 253 records · Page 14Linked to original sources
USGS2022

Assessing vegetation recovery from energy development using a dynamic reference approach

Ecologically relevant references are useful for evaluating ecosystem recovery, but references that are temporally static may be less useful when environmental conditions and disturbances are spatially and temporally heterogeneous. This challenge is particularly acute for ecosystems dominated by sagebrush ( Artemisia spp.), where communities may require decades to recover from disturbance. We demonstrated application of a dynamic reference approach to studying sagebrush recovery using three decades of sagebrush cover estimates from remote sensing (1985–2018). We modelled recovery on former oil and gas well pads ( n = 1200) across southwestern Wyoming, USA, relative to paired references identified by the Disturbance Automated Reference Toolset. We also used quantile regression to account for unmodelled heterogeneity in recovery, and projected recovery from similar disturbance across the landscape. Responses to weather and site-level factors often differed among quantiles, and sagebrush recovery on former well pads increased more when paired reference sites had greater sagebrush cover. Little (<5%) of the landscape was projected to recover within 100 years for low to mid quantiles, and recovery often occurred at higher elevations with cool and moist annual conditions. Conversely, 48%–78% of the landscape recovered quickly (within 25 years) for high quantiles of sagebrush cover. Our study demonstrates advantages of using dynamic reference sites when studying vegetation recovery, as well as how additional inferences obtained from quantile regression can inform management.

Wyoming↗
USGS2024

Solute export patterns across the contiguous USA

Understanding controls on solute export to streams is challenging because heterogeneous catchments can respond uniquely to drivers of environmental change. To understand general solute export patterns, we used a large-scale inductive approach to evaluate concentration–discharge (C–Q) metrics across catchments spanning a broad range of catchment attributes and hydroclimatic drivers. We leveraged paired C–Q data for 11 solutes from CAMELS-Chem, a database built upon an existing dataset of catchment and hydroclimatic attributes from relatively undisturbed catchments across the contiguous USA. Because C–Q relationships with Q thresholds reflect a shift in solute export dynamics and are poorly characterized across solutes and diverse catchments, we analysed C–Q relationships using Bayesian segmented regression to quantify Q thresholds in the C–Q relationship. Threshold responses were rare, representing only 12% of C–Q relationships, 56% of which occurred for solutes predominantly sourced from bedrock. Further, solutes were dominated by one or two C–Q patterns that reflected vertical solute–source distributions. Specifically, solutes predominantly sourced from bedrock had diluting C–Q responses in 43%–70% of catchments, and solutes predominantly sourced from soils had more enrichment responses in 35%–51% of catchments. We also linked C–Q relationships to catchment and hydroclimatic attributes to understand controls on export patterns. The relationships were generally weak despite the diversity of solutes and attribute types considered. However, catchment and hydroclimatic attributes in the central USA typically drove the most divergent export behaviour for solutes. Further, we illustrate how our inductive approach generated new hypotheses that can be tested at discrete, representative catchments using deductive approaches to better understand the processes underlying solute export patterns. Finally, given these long-term C–Q relationships are from minimally disturbed catchments, our findings can be used as benchmarks for change in more disturbed catchments.

contiguous United States↗
USGS2020

Keeping up with the times: Mapping range-wide habitat suitability for endangered species in a changing environment

Biologists and policy-makers have the difficult task of allocating limited resources to habitat conservation and management for endangered species in the face of changing environmental conditions. Satellite remote sensing can inform conservation because it is an efficient means to obtain environmental data over broad spatial and temporal extents. Yet, the challenges of accessing, processing, and analyzing remote sensing data hinder wider application of these techniques in conservation planning. We used Landsat data and hierarchical statistical models to link satellite-derived habitat measurements with abundance of endangered Yuma Ridgway's rails ( Rallus obsoletus yumanensis ) within the Lower Colorado River Basin and Salton Sink, USA. We addressed many of the challenges facing the application of remote sensing techniques by using the web-based, freely-available Google Earth Engine to process Landsat datasets, apply habitat models, and generate maps to predict habitat suitability at a fine spatial grain (30 m) across the range of the species. These maps are shareable, interactive, and easy to update annually as habitat conditions change using a Google Earth Engine App we developed. Thus, we provide a framework for building habitat suitability models and maps to help target adaptive habitat management over broad extents for sensitive species, enabling biologists to improve conservation and restoration efforts regularly as conditions change in highly variable ecosystems. We demonstrate this approach for Yuma Ridgway's rails, but our methods for merging hierarchical statistical models with open-source mapping software to describe spatial-temporal heterogeneity in habitat quality are applicable to any species, and are especially helpful to species inhabiting highly variable ecosystems.

Arizona, California, Nevada↗
USGS2019

Influence of climate, post‐treatment weather extremes, and soil factors on vegetation recovery after restoration treatments in the southwestern US

Aims Understanding the conditions associated with dryland vegetation recovery after restoration treatments is challenging due to a lack of monitoring data and high environmental variability over time and space. Tracking recovery trajectories with satellite‐based vegetation indices can strengthen predictions of restoration outcomes across broad areas with varying environmental conditions. Location Southwestern United States. Methods We quantified the recovery trajectories of spring and summer soil‐adjusted total vegetation index (SATVI) for 5 to 10 year periods following post‐wildfire seeding or prescribed burns for 241 treatment sites, and related SATVI to ground‐based vegetation cover. We modeled SATVI based on time since treatment, yearly temperature and precipitation, weather extremes following treatment, soil available water capacity, invasive species presence, and treatment type. We also tested for the effects of environmental variables on trajectories, by examining interactions with years post‐treatment. Results Ground‐based vegetation cover and SATVI were highly correlated. Most treatment sites had positive recovery rates for spring (82%) and summer (85%) SATVI. Several environmental variables affected vegetation recovery trajectories as indicated by interactions with time since treatment. Yearly warm season precipitation had a positive effect on SATVI recovery that increased over time, whereas the positive effect of extreme high warm season precipitation following treatment decreased over time for both seasons of vegetation measurements. For spring SATVI, the positive effect of cool season yearly precipitation increased over time while the negative effect of extreme high temperatures following treatment became more negative over time. Invasive species presence led to higher spring, but not summer, SATVI. Conclusions Satellite‐based remote sensing is a promising tool to assess vegetation recovery following restoration treatments, particularly when it is combined with ground‐based monitoring. Our results suggest that weather extremes following restoration treatments can affect vegetation recovery trajectories and should be considered in decisions such as the timing of restoration treatments.

Applied Vegetation Science↗
USGS2010

Evidence for a temperature acclimation mechanism in bacteria: an empirical test of a membrane-mediated trade-off

1. Shifts in bacterial community composition along temporal and spatial temperature gradients occur in a wide range of habitats and have potentially important implications for ecosystem functioning. However, it is often challenging to empirically link an adaptation or acclimation that defines environmental niche or biogeography with a quantifiable phenotype, especially in micro-organisms. 2. Here we evaluate a possible mechanistic explanation for shifts in bacterioplankton community composition in response to temperature by testing a previously hypothesized membrane mediated trade-off between resource acquisition and respiratory costs. 3. We isolated two strains of Flavobacterium sp. at two temperatures (cold isolate and warm isolate) from the epilimnion of a small temperate lake in North Central Minnesota. 4. Compared with the cold isolate the warm isolate had higher growth rate, higher carrying capacity, lower lag time and lower respiration at the high temperature and lower phosphorus uptake at the low temperature. We also observed significant differences in membrane lipid composition between isolates and between environments that were consistent with adjustments necessary to maintain membrane fluidity at different temperatures. 5. Our results suggest that temperature acclimation in planktonic bacteria is, in part, a resource-dependent membrane-facilitated phenomenon. This study provides an explicit example of how a quantifiable phenotype can be linked through physiology to competitive ability and environmental niche.

Functional Ecology↗
USGS2013

The SAFRR (Science Application for Risk Reduction) Tsunami Scenario

The Science Application for Risk Reduction (SAFRR) tsunami scenario depicts a hypothetical but plausible tsunami created by an earthquake offshore from the Alaska Peninsula and its impacts on the California coast. The tsunami scenario is a collaboration between the U.S. Geological Survey (USGS), the California Geological Survey (CGS), the California Governor’s Office of Emergency Services (Cal OES), the National Oceanic and Atmospheric Administration (NOAA), other Federal, State, County, and local agencies, private companies, and academic and other institutions. This document presents evidence for past tsunamis, the scientific basis for the source, likely inundation areas, current velocities in key ports and harbors, physical damage and repair costs, economic consequences, environmental and ecological impacts, social vulnerability, emergency management and evacuation challenges, and policy implications for California associated with this hypothetical tsunami. We also discuss ongoing mitigation efforts by the State of California and new communication products. The intended users are those who need to make mitigation decisions before future tsunamis, and those who will need to make rapid decisions during tsunami events. The results of the tsunami scenario will help managers understand the context and consequences of their decisions and how they may improve preparedness and response. An evaluation component will assess the effectiveness of the scenario process for target stakeholders in a separate report to improve similar efforts in the future.

Open-File Report↗
USGS2013

SAFRR (Science Application for Risk Reduction) Tsunami Scenario--Executive Summary and Introduction: Chapter A in The SAFRR (Science Application for Risk Reduction) Tsunami Scenario

The Science Application for Risk Reduction (SAFRR) tsunami scenario depicts a hypothetical but plausible tsunami created by an earthquake offshore from the Alaska Peninsula and its impacts on the California coast. The tsunami scenario is a collaboration between the U.S. Geological Survey (USGS), the California Geological Survey, the California Governor’s Office of Emergency Services (Cal OES), the National Oceanic and Atmospheric Administration (NOAA), other Federal, State, County, and local agencies, private companies, and academic and other institutions. This document presents evidence for past tsunamis, the scientific basis for the source, likely inundation areas, current velocities in key ports and harbors, physical damage and repair costs, economic consequences, environmental and ecological impacts, social vulnerability, emergency management and evacuation challenges, and policy implications for California associated with this hypothetical tsunami. We also discuss ongoing mitigation efforts by the State of California and new communication products. The intended users are those who need to make mitigation decisions before future tsunamis, and those who will need to make rapid decisions during tsunami events. The results of the tsunami scenario will help managers understand the context and consequences of their decisions and how they may improve preparedness and response. An evaluation component will assess the effectiveness of the scenario process for target stakeholders in a separate report to improve similar efforts in the future.

California↗
USGS2020

Density dependence and adult survival drive the dynamics in two high elevation amphibian populations

Amphibian conservation has progressed from the identification of declines to mitigation, but efforts are hampered by the lack of nuanced information about the effects of environmental characteristics and stressors on mechanistic processes of population regulation. Challenges include a paucity of long-term data and scant information about the relative roles of extrinsic (e.g., weather) and intrinsic (e.g., density dependence) factors. We used a Bayesian formulation of an open population capture-recapture model and >30 years of data to examine intrinsic and extrinsic factors regulating two adult boreal chorus frogs ( Pseudacris maculata ) populations. We modelled population growth rate and apparent survival directly, assessed their temporal variability, and derived estimates of recruitment. Populations were relatively stable (geometric mean population growth rate >1) and regulated by negative density dependence (i.e., higher population sizes reduced population growth rate). In the smaller population, density dependence also acted on adult survival. In the larger population, higher population growth was associated with warmer autumns. Survival estimates ranged from 0.30–0.87, per-capita recruitment was <1 in most years, and mean seniority probability was >0.50, suggesting adult survival is more important to population growth than recruitment. Our analysis indicates density dependence is a primary driver of population dynamics for P. maculata adults.

Colorado↗
USGS2020

USGS Telemetry Project

Telemetry of acoustically tagged bigheaded carp (i.e., bighead carp Hypophthalmichthys nobilis and silver carp H. molitrix ) and surrogate fish species has become an invaluable tool in management for these species in the upper Illinois Waterway Systems (i.e., upper Illinois River, lower Des Plaines River, and Chicago Area Waterway System). For example, movement probabilities between adjacent navigation pools need to be estimated to parameterize the Spatially Explicit Asian Carp Population Model (SEAcarP). SEAcarP is a population model used in scenario planning by the Monitoring and Response Workgroup (MRWG) to evaluate alternative management actions. These movement probabilities are estimated from the telemetry data obtained from a longitudinal network of strategically placed receivers that detect bigheaded carp that have been implanted with acoustic transmitters. In addition, fish removal by contracted fishers has become the primary method of controlling bigheaded carp in the upper Illinois and lower Des Plaines Rivers. Variable patterns in bigheaded carp distribution, habitat, and movement, influenced by seasonal and environmental conditions, make targeting bigheaded carp for removal and containment challenging and costly. Understanding these movement patterns for bigheaded carp through modeling and real-time telemetry applications informs removal efforts and facilitates monitoring and contingency actions based on fish movements. To develop a better understanding of fish movement dynamics to meet management objectives, an existing network of real-time and data-logging acoustic receivers in the upper Illinois Waterway Systems is collaboratively managed by a multi-agency team (see Participating Agencies section above). A Telemetry Workgroup has been established by the MRWG to ensure that the multi-agency telemetry efforts are coordinated to efficiently and effectively meet the MRWG goals. This workgroup plans and executes the placement of receivers, tagging of bigheaded carp with acoustic tags, and management of the telemetry data. Three primary objectives to meet MRWG goals identified by the Telemetry Workgroup included (1) development of a common standardized telemetry database with visualization and analysis tools, (2) transitioning from Program MARK (http://www.phidot.org/software/mark/) to a custom Bayesian multi-state model for estimating movement probabilities needed for SEAcarP and (3) deploying, maintaining, and serving data from real-time acoustic receivers to inform contingency planning and fish removal. A telemetry database and visualization tools (FishTracks) will facilitate standardization, archiving, sharing, quality assurance, visualization and analysis of the telemetry data needed for management. Modifications and additions to FishTracks will facilitate more problem-free use of the database and associated applications, as well as useful extraction of information to meet management goals. The transition to a custom Bayesian multi-state model to estimate movement probabilities will support more efficient, effective, and robust population modeling with SEAcarP by overcoming short comings of Program MARK for this purpose. These shortcomings include lack of customizability and extensibility, problems of singularities and poor-convergence, software crashes, parameter exclusion from models, an inability to consistently generate estimates of movement probability, and a lack of uncertainty estimates for movement probabilities. A real-time receiver network that is maintained and tested annually will ensure reliability and accuracy of the real-time alerts to bigheaded carp movements that can be used by management to plan contingency actions.

Illinois↗
USGS2023

USGS telemetry project

Tagging bigheaded carp (i.e., Bighead Carp and Silver Carp) and surrogate fish species with acoustic transmitters has become an invaluable management tool in the Upper IWW (i.e., upper Illinois River, lower Des Plaines River, and the CAWS). For example, movement probabilities between adjacent navigation pools need to be estimated to parameterize models, such as the SEICarP Model—a population model used in scenario planning by the MRWG to evaluate alternative management actions (Kallis et al. 2023). These movement probabilities are estimated from the telemetry data obtained from a longitudinal network of strategically placed receivers that detect bigheaded carp that have been implanted with acoustic transmitters (i.e., tagged). In addition, fish removal by contracted fishers has become the primary method of controlling bigheaded carp in the upper Illinois and lower Des Plaines rivers. Variable patterns in bigheaded carp distribution, habitat, and movement, influenced by seasonal and environmental conditions, make targeting bigheaded carp for removal and containment challenging and costly. Understanding these movement patterns for bigheaded carp through modeling and real-time telemetry applications informs removal efforts and facilitates monitoring and contingency actions based on fish movements.

Illinois↗
USGS2024

The Ecosystem Approach in the 21st century: Guiding science and management – A synthesis

Maintaining the integrity and health of aquatic ecosystems is critical to sustaining the many valued services that they provide society. Unfortunately, achieving this goal has proven challenging in most of the world's large ecosystems owing to rampant environmental change caused by human-driven stress, including accelerating climate change, pollution of waterways, habitat modification and destruction, and the continued spread of non-native species (He and Silliman, 2019; Jenny et al., 2020; Smith et al., 2015; Steffen et al., 2007). These stressors, which can also include purposeful management actions (e.g. nutrient and fisheries management), are presenting a grave challenge globally to efforts aimed at securing a sustainable future for nature, society, and the economy.

Aquatic Ecosystem Health & Management↗
USGS2021

Water storage decisions will determine the distribution and persistence of imperiled river fishes

Managing the world’s freshwater supply to meet societal and environmental needs in a changing climate is one of the biggest challenges for the 21 st century. Dams provide water security, however, the allocation of dwindling water supply among reservoirs could exacerbate or ameliorate the effects of climate change on aquatic communities. Here, we show that the relative sensitivity of river thermal regimes to direct impacts of climate change and societal decisions concerning water storage vary substantially throughout a river basin. In the absence of interspecific interactions, future Colorado River temperatures would appear to benefit both endemic and nonnative fish species. However, endemic species are already declining or extirpated in locations where their ranges overlap with warmwater nonnatives and changes in water storage may lead to warming in some of the coolest portions of the river basin, facilitating further nonnative expansion. Integrating environmental considerations into ongoing water storage negotiations may lead to better resource outcomes than mitigating nonnative species impacts after the fact.

Ecological Applications↗
USGS2014

Reflections on a vision for integrated research and monitoring after 15 years

In May of 1998, Owen Bricker and his co-author Michael Ruggiero introduced a conceptual design for integrating the Nation’s environmental research and monitoring programs. The Framework for Integrated Monitoring and Related Research was an organizing strategy for relating data collected by various programs, at multiple spatial and temporal scales, and by multiple science disciplines to solve complex ecological issues that individual research or monitoring programs were not designed to address. The concept nested existing intensive monitoring and research stations within national and regional surveys, remotely sensed data, and inventories to produce a collaborative program for multi-scale, multi-network integrated environmental monitoring and research. Analyses of gaps in data needed for specific issues would drive decisions on network improvements or enhancements. Data contributions to the Framework from existing networks would help indicate critical research and monitoring programs to protect during budget reductions. Significant progress has been made since 1998 on refining the Framework strategy. Methods and models for projecting scientific information across spatial and temporal scales have been improved, and a few regional pilots of multi-scale data-integration concepts have been attempted. The links between science and decision-making are also slowly improving and being incorporated into science practice. Experiments with the Framework strategy since 1998 have revealed the foundational elements essential to its successful implementation, such as defining core measurements, establishing standards of data collection and management, integrating research and long-term monitoring, and describing baseline ecological conditions. They have also shown us the remaining challenges to establishing the Framework concept: protecting and enhancing critical long-term monitoring, filling gaps in measurement methods, improving science for decision support, and integrating the disparate integrated science efforts now underway. In the 15 years since the Bricker and Ruggiero (Ecol Appl 8(2):326–329, 1998) paper challenged us with a new paradigm for bringing sound and comprehensive science to environmental decisions, the scientific community can take pride in the progress that has been made, while also taking stock of the challenges ahead for completing the Framework vision.

Aquatic Geochemistry↗
USGS2017

Future of Pacific salmon in the face of environmental change: Lessons from one of the world's remaining productive salmon regions

Pacific salmon Oncorhynchus spp. face serious challenges from climate and landscape change, particularly in the southern portion of their native range. Conversely, climate warming appears to be allowing salmon to expand northwards into the Arctic. Between these geographic extremes, in the Gulf of Alaska region, salmon are at historically high abundances but face an uncertain future due to rapid environmental change. We examined changes in climate, hydrology, land cover, salmon populations, and fisheries over the past 30–70 years in this region. We focused on the Kenai River, which supports world-famous fisheries but where Chinook Salmon O. tshawytscha populations have declined, raising concerns about their future resilience. The region is warming and experiencing drier summers and wetter autumns. The landscape is also changing, with melting glaciers, wetland loss, wildfires, and human development. This environmental transformation will likely harm some salmon populations while benefiting others. Lowland salmon streams are especially vulnerable, but retreating glaciers may allow production gains in other streams. Some fishing communities harvest a diverse portfolio of fluctuating resources, whereas others have specialized over time, potentially limiting their resilience. Maintaining diverse habitats and salmon runs may allow ecosystems and fisheries to continue to thrive amidst these changes.

Alaska↗
USGS2016

The challenges and opportunities in cumulative effects assessment

The cumulative effects of increasing human use of the ocean and coastal zone have contributed to a rapid decline in ocean and coastal resources. As a result, scientists are investigating how multiple, overlapping stressors accumulate in the environment and impact ecosystems. These investigations are the foundation for the development of new tools that account for and predict cumulative effects in order to more adequately prevent or mitigate negative effects. Despite scientific advances, legal requirements, and management guidance, those who conduct assessments—including resource managers, agency staff, and consultants—continue to struggle to thoroughly evaluate cumulative effects, particularly as part of the environmental assessment process. Even though 45 years have passed since the United States National Environmental Policy Act was enacted, which set a precedent for environmental assessment around the world, defining impacts, baseline, scale, and significance are still major challenges associated with assessing cumulative effects. In addition, we know little about how practitioners tackle these challenges or how assessment aligns with current scientific recommendations. To shed more light on these challenges and gaps, we undertook a comparative study on how cumulative effects assessment (CEA) is conducted by practitioners operating under some of the most well-developed environmental laws around the globe: California, USA; British Columbia, Canada; Queensland, Australia; and New Zealand. We found that practitioners used a broad and varied definition of impact for CEA, which led to differences in how baseline, scale, and significance were determined. We also found that practice and science are not closely aligned and, as such, we highlight opportunities for managers, policy makers, practitioners, and scientists to improve environmental assessment.

Environmental Impact Assessment Review↗
USGS2022

Global genetic diversity status and trends: Towards a suite of Essential Biodiversity Variables (EBVs) for genetic composition

Biodiversity underlies ecosystem resilience, ecosystem function, sustainable economies, and human well-being. Understanding how biodiversity sustains ecosystems under anthropogenic stressors and global environmental change will require new ways of deriving and applying biodiversity data. A major challenge is that biodiversity data and knowledge are scattered, biased, collected with numerous methods, and stored in inconsistent ways. The Group on Earth Observations Biodiversity Observation Network (GEO BON) has developed the Essential Biodiversity Variables (EBVs) as fundamental metrics to help aggregate, harmonize, and interpret biodiversity observation data from diverse sources. Mapping and analyzing EBVs can help to evaluate how aspects of biodiversity are distributed geographically and how they change over time. EBVs are also intended to serve as inputs and validation to forecast the status and trends of biodiversity, and to support policy and decision making. Here, we assess the feasibility of implementing Genetic Composition EBVs (Genetic EBVs), which are metrics of within-species genetic variation. We review and bring together numerous areas of the field of genetics and evaluate how each contributes to global and regional genetic biodiversity monitoring with respect to theory, sampling logistics, metadata, archiving, data aggregation, modeling, and technological advances. We propose four Genetic EBVs: ( i ) Genetic Diversity; ( ii ) Genetic Differentiation; ( iii ) Inbreeding; and ( iv ) Effective Population Size ( N e ). We rank Genetic EBVs according to their relevance, sensitivity to change, generalizability, scalability, feasibility and data availability. We outline the workflow for generating genetic data underlying the Genetic EBVs, and review advances and needs in archiving genetic composition data and metadata. We discuss how Genetic EBVs can be operationalized by visualizing EBVs in space and time across species and by forecasting Genetic EBVs beyond current observations using various modeling approaches. Our review then explores challenges of aggregation, standardization, and costs of operationalizing the Genetic EBVs, as well as future directions and opportunities to maximize their uptake globally in research and policy. The collection, annotation, and availability of genetic data has made major advances in the past decade, each of which contributes to the practical and standardized framework for large-scale genetic observation reporting. Rapid advances in DNA sequencing technology present new opportunities, but also challenges for operationalizing Genetic EBVs for biodiversity monitoring regionally and globally. With these advances, genetic composition monitoring is starting to be integrated into global conservation policy, which can help support the foundation of all biodiversity and species' long-term persistence in the face of environmental change. We conclude with a summary of concrete steps for researchers and policy makers for advancing operationalization of Genetic EBVs. The technical and analytical foundations of Genetic EBVs are well developed, and conservation practitioners should anticipate their increasing application as efforts emerge to scale up genetic biodiversity monitoring regionally and globally.

Biological Reviews↗
USGS2008

Distribution of geogenic arsenic in hydrologic systems: Controls and challenges

The presence of elevated concentration of arsenic (As) in natural hydrologic systems is regarded as the most formidable environmental crisis in the contemporary world. With its substantial presence in the drinking water of more than thirty countries worldwide, and with an affected population of more than 100 million, it has been termed as the largest mass poisoning in human history. In this special issue, we have tried to provide the most recent research advances on controls and challenges of this severe groundwater contaminant. The articles in this issue, originally presented in the 2006 Geological Society of America Annual Meeting, address the distribution of As in various geologic and geographic settings, the controls of redox and other geochemical parameters on its spatial and temporal variability, the influence of sedimentology and stratigraphy on its occurrence, and mechanisms controlling its mobility. The knowledge available from these studies should provide a roadmap for future research in arsenic contamination hydrology.

Journal of Contaminant Hydrology↗
USGS2013

Data management challenges in species distribution modeling

An important component in the fields of ecology and conservation biology is understanding the environmental conditions and geographic areas that are suitable for a given species to inhabit. A common tool in determining such areas is species distribution modeling which uses computer algorithms to determine the spatial distribution of organisms. Most commonly the correlative relationships between the organism and environmental variables are the primary consideration. The data requirements for this type of modeling consist of known presence and possibly absence locations of the species as well as the values of environmental or climatic covariates thought to define the species habitat suitability at these locations. These covariate data are generally extracted from remotely sensed imagery, interpolated/gridded historical climate data, or downscaled climate model output. Traditionally, ecologists and biologists have constructed species distribution models using workflows and data that reside primarily on their local workstations or networks. This workflow is becoming challenging as scientists increasingly try to use these modeling techniques to inform management decisions under different climate change scenarios. This challenge stems from the fact that remote sensing products, gridded historical climate, and downscaled climate models are not only increasing in spatial and temporal resolution but proliferating as well. Any rigorous assessment of uncertainty requires a computationally intensive sensitivity analysis accounting for various sources of uncertainty. The scientists fitting these models generally do not have the background in computer science required to take advantage of recent advances in web-service based data acquisition, remote high-powered data processing, or scientific workflow systems. Ecologists in the field of modeling are in need of a tractable platform that abstracts the inherent computational complexity required to incorporate the burgeoning field of coupled climate and ecological response modeling. In this paper we describe the computational challenges in species distribution modeling and solutions using scientific workflow systems. We focus on the Software for Assisted Species Modeling (SAHM) a package within VisTrails, an open-source scientific workflow system.

Bulletin of the Technical Committee on Data Engine↗