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USGS2021

Determination of burn severity models ranging from regional to continental scales for the conterminous United States

Identifying meaningful measures of ecological change over large areas is dependent on the quantification of robust relationships between ecological metrics and remote sensing products. Over the past several decades, ground observations of wildfire and prescribed fire severity have been acquired across hundreds of wildland fires in the United States, primarily utilizing the Composite Burn Index (CBI) plot protocol. These observations have been coupled to spaceborne passive spectral reflectance indices (e.g. Landsat-derived variations of the Normalized Burn Ratio [NBR]) to produce regression models describing their relationship. Here we develop regression models by vegetation type for multiple vegetation classification systems representing a range of spatial scales, and a decision tree framework for evaluating these regression models. Our overall goals were to determine which scale of ecological classifications provided the best estimate of burn severity from Landsat data and how to choose the best regression model. We aggregated a total of 6280 CBI plots for 234 wildland fires that burned between 1994 and 2017 and produced Landsat-derived NBR and differenced NBR (dNBR) values for each plot. We then calculated best fit linear or higher order regression equations between CBI and NBR/dNBR for each landcover classification system from smallest to largest scale: LANDFIRE Biophysical Settings (BPS), National Vegetation Classification macrogroup (NVC) landcover classifications, Omernick III, II, and I ecoregions, LANDFIRE Fire Regime Groups (FRG), and the entire conterminous United States (CONUS) dataset. The CONUS regression model goodness of fit was moderate (R 2 = 0.55, P < 0.001) for dNBR and poor (R 2 = 0.30, P < 0.001) for NBR. Within landcover classifications, CBI was better fit by dNBR than NBR. Finer scale regional regression models including BPS (dNBR R 2 ¯ "> R2¯ = 0.56 and 0.00–0.83 R 2 range; NBR R 2 ¯ "> R(bar) 2 = 0.43 and 0.00–0.82 R 2 range) and NVC (dNBR R 2 ¯ "> R(bar) 2 = 0.55 and 0.15–0.78 R 2 range; NBR R 2 ¯ "> R(bar) 2 = 0.41 and 0.00–0.79 R 2 range) were on average the same or better than the CONUS models for dNBR and NBR, with the strongest fit models exhibiting R 2 ≥ 0.70, whereas larger scale regional models R 2 ¯ "> R(bar) 2 ranged from 0.28 to 0.5. However, variation in accuracy among landcover types indicate that dNBR and NBR regression models could be used to effectively estimate CBI for future fires in certain regions, while for other regions models may require additional field observations or alternative spectral transformations. Our decision tree schema can be used to help users determine which scale is likely to produce the most accurate results using our models. The CBI regression models developed here, paired with the decision tree, provide users with a simple method to estimate burn severity in units of CBI for any fire within CONUS with moderate to high levels of confidence and provide a template for further development of models with new data going forward.

Conterminous United States↗

USGS2019

Statistical power of dynamic occupancy models to identify temporal change: Informing the North American Bat Monitoring Program

Dynamic occupancy models provide a flexible framework for estimating and mapping species occupancy patterns over space and time for large-scale monitoring programs (e.g., the North American Bat Monitoring Program (NABat), the Amphibian Research and Monitoring Initiative). Challenges for designing surveys using the dynamic occupancy modeling framework include defining appropriate derived trend parameters, and providing usable tools for researchers to conduct project-specific sample size investigations. We present a simulation-based power analysis framework for dynamic occupancy models that allows for the incorporation of the underlying environmental space (i.e., as covariates) within a specific study region to inform sample size estimation. We investigate two definitions of temporal trend: (1) a gradual, sustained (linear or nonlinear) change over a period of many years, and (2) an abrupt increase or decrease between two time periods. We draw upon pilot data collected following NABat protocols to inform assumed data generating values in a demonstration of our approach. Due to the complicated parameter structure of dynamic occupancy models, we emphasize the importance of visualizing simulated changes over time based on different parameter settings prior to conducting a power analysis. Our simulations revealed that the linearity of short-term trends (five years in our investigation) conferred higher power with lower sample size than longer trends where occupancy probabilities approached zero (ten years in our investigation). We provide an example of how to use our tools to conduct customized investigations using questions posed by NABat, and in doing so, we shed light on general guidelines that can be applied to programs monitoring species occupancy for other taxa. Importantly, we created an R package to execute our approach for informing program-, species-, and study-specific investigations aimed at identifying changes in species occupancy.

Ecological Indicators↗

USGS2016

Model description and evaluation of the mark-recapture survival model used to parameterize the 2012 status and threats analysis for the Florida manatee ( Trichechus manatus latirostris )

This report provides supporting details and evidence for the rationale, validity and efficacy of a new mark-recapture model, the Barker Robust Design, to estimate regional manatee survival rates used to parameterize several components of the 2012 version of the Manatee Core Biological Model (CBM) and Threats Analysis (TA). The CBM and TA provide scientific analyses on population viability of the Florida manatee subspecies ( Trichechus manatus latirostris ) for U.S. Fish and Wildlife Service’s 5-year reviews of the status of the species as listed under the Endangered Species Act. The model evaluation is presented in a standardized reporting framework, modified from the TRACE (TRAnsparent and Comprehensive model Evaluation) protocol first introduced for environmental threat analyses. We identify this new protocol as TRACE-MANATEE SURVIVAL and this model evaluation specifically as TRACE-MANATEE SURVIVAL, Barker RD version 1. The longer-term objectives of the manatee standard reporting format are to (1) communicate to resource managers consistent evaluation information over sequential modeling efforts; (2) build understanding and expertise on the structure and function of the models; (3) document changes in model structures and applications in response to evolving management objectives, new biological and ecological knowledge, and new statistical advances; and (4) provide greater transparency for management and research review.

Open-File Report↗

USGS2011

An inventory and monitoring plan for a Sonoran Desert ecosystem; Barry M. Goldwater Range-West

Marine Corps Air Station Yuma manages the Barry M. Goldwater Range-West, which encompasses approximately 2,800 square kilometers of Sonoran Desert habitat in southwestern Arizona. The Barry M. Goldwater Range is a major U.S. military installation designed as an air combat training location for the U.S. Marine Corps and U.S. Air Force, but it also includes some of the most pristine desert habitat in the United States. In an effort to ensure the long-term viability of this unique natural resource, the U.S. Geological Survey (USGS) has developed an Integrated Natural Resources Management Plan and Inventory and Monitoring Plan to guide natural resource management of the Barry M. Goldwater Range-West. This Inventory and Monitoring Plan provides a framework for long-term ecosystem monitoring on Barry M. Goldwater Range-West lands by identifying existing and potential threats to ecosystem function, prioritizing resources for monitoring, and providing information and protocols necessary to initiate a long-term ecosystem monitoring program. The Inventory and Monitoring Plan and related protocols were developed through extensive review of existing Sonoran Desert monitoring programs and monitoring literature and through a 2-day workshop with resource managers, monitoring experts, and other stakeholders. The Barry M. Goldwater Range-West Inventory and Monitoring Plan stresses the importance of regional monitoring partnerships and protocol standardization for understanding landscape-scale ecosystem changes in the Sonoran Desert; information and protocols contained within the plan may also be of interest to land managers engaged in large-scale ecosystem monitoring and adaptive management of other arid regions.

Open-File Report↗

USGS2022

A framework for ensemble modelling of climate change impacts on lakes worldwide: The ISIMIP lake sector.

Empirical evidence demonstrates that lakes and reservoirs are warming across the globe. Consequently, there is an increased need to project future changes in lake thermal structure and resulting changes in lake biogeochemistry in order to plan for the likely impacts. Previous studies of the impacts of climate change on lakes have often relied on a single model forced with limited scenario-driven projections of future climate for a relatively small number of lakes. As a result, our understanding of the effects of climate change on lakes is fragmentary, based on scattered studies using different data sources and modelling protocols, and mainly focused on individual lakes or lake regions. This has precluded identification of the main impacts of climate change on lakes at global and regional scales and has likely contributed to the lack of lake water quality considerations in policy-relevant documents, such as the Assessment Reports of the Intergovernmental Panel on Climate Change (IPCC). Here, we describe a simulation protocol developed by the Lake Sector of the Inter-Sectoral Impact Model Intercomparison Project (ISIMIP) for simulating climate change impacts on lakes using an ensemble of lake models and climate change scenarios for ISIMIP phases 2 and 3. The protocol prescribes lake simulations driven by climate forcing from gridded observations and different Earth system models under various representative greenhouse gas concentration pathways (RCPs), all consistently bias-corrected on a 0.5 ∘ × 0.5 ∘ global grid. In ISIMIP phase 2, 11 lake models were forced with these data to project the thermal structure of 62 well-studied lakes where data were available for calibration under historical conditions, and using uncalibrated models for 17 500 lakes defined for all global grid cells containing lakes. In ISIMIP phase 3, this approach was expanded to consider more lakes, more models, and more processes. The ISIMIP Lake Sector is the largest international effort to project future water temperature, thermal structure, and ice phenology of lakes at local and global scales and paves the way for future simulations of the impacts of climate change on water quality and biogeochemistry in lakes.

Geoscientific Model Development↗

USGS2011

An approach to regional wetland digital elevation model development using a differential global positioning system and a custom-built helicopter-based surveying system

Accurate topographic data are critical to restoration science and planning for the Everglades region of South Florida, USA. They are needed to monitor and simulate water level, water depth and hydroperiod and are used in scientific research on hydrologic and biologic processes. Because large wetland environments and data acquisition challenge conventional ground-based and remotely sensed data collection methods, the United States Geological Survey (USGS) adapted a classical data collection instrument to global positioning system (GPS) and geographic information system (GIS) technologies. Data acquired with this instrument were processed using geostatistics to yield sub-water level elevation values with centimetre accuracy (±15 cm). The developed database framework, modelling philosophy and metadata protocol allow for continued, collaborative model revision and expansion, given additional elevation or other ancillary data.

Florida↗

USGS2015

Combining split-beam and dual-frequency identification sonars to estimate abundance of anadromous fishes in the Roanoke River, North Carolina

Riverine hydroacoustic techniques are an effective method for evaluating abundance of upstream migrating anadromous fishes. To use these methods in the Roanoke River, North Carolina, at a wide site with uneven bottom topography, we used a combination of split-beam sonar and dual-frequency identification sonar (DIDSON) deployments. We aimed a split-beam sonar horizontally to monitor midchannel and near-bottom zones continuously over the 3-month spring monitoring periods in 2010 and 2011. The DIDSON was rotated between seven cross-channel locations (using a vertical aim) and nearshore regions (using horizontal aims). Vertical deployment addressed blind spots in split-beam coverage along the bottom and provided reliable information about the cross-channel and vertical distributions of upstream migrants. Using a Bayesian framework, we modeled sonar counts within four cross-channel strata and apportioned counts by species using species proportions from boat electrofishing and gill netting. Modeled estimates (95% credible intervals [CIs]) of total upstream migrants in 2010 and 2011 were 2.5 million (95% CI, 2.4–2.6 million) and 3.6 million (95% CI, 3.4–3.9 million), respectively. Results indicated that upstream migrants are extremely shore- and bottom-oriented, suggesting nearshore DIDSON monitoring improved the accuracy and precision of our estimates. This monitoring protocol and model may be widely applicable to river systems regardless of their cross-sectional width or profile.

North American Journal of Fisheries Management↗

USGS2024

Milkweed and floral resource availability for monarch butterflies (Danaus plexippus) in the United States

The global decline of pollinators, particularly insects, underscores the importance of enhanced monitoring of their populations and habitats. However, monitoring some pollinator habitat is challenging due to widespread species distributions and shifts in habitat requirements through seasons and life stages. The monarch butterfly ( Danaus plexippus ), a migratory insect pollinator that breeds widely throughout North America, presents a unique case study for testing a sampling framework to overcome these challenges. Monarchs exhibit discrete resource needs across life stages (e.g., larval requirement for milkweed, adult requirement for floral nectar), utilizing many land use types across their extensive geographic range during breeding and migration seasons. The Integrated Monarch Monitoring Program (IMMP) uses a standardized protocol with a generalized random tessellation stratified (GRTS) sampling design to gather spatially balanced and ecologically representative information on monarch habitats within the United States. The IMMP is applicable to various land use types and habitats used by breeding monarchs and may be extended to sites outside of the GRTS design to collect data on non-random sites of interest, such as legacy or conservation sites. Additionally, the IMMP’s modular design and publicly available training allows for broad participation, including involvement from community scientists. Here, we summarize habitat metrics (milkweed and floral resources) across 1,233 sites covering much of the monarch’s breeding range. We examine variation in milkweed density and floral resource availability on probabilistic (random) and non-probabilistic (convenience) samples and among land use types (site types). Additionally, we assess resource availability within core geographies for monarch breeding and migration, specifically within the U.S. Fish and Wildlife Service’s Monarch Conservation Units (western, northern, and southern United States). Milkweed density, floral frequency, and floral richness were higher on non-random sites and in the North region. Among site types, milkweed density was highest on Rights-of-Way and Unclassified Grassland, while floral frequency was lowest on Rights-of-Way. The IMMP represents the first field-based habitat monitoring program of this scale for monarchs, yielding a robust dataset on monarchs and their habitats across their breeding range and offering a framework for surveying the habitat of insect species with diverse habitat requirements or widespread distributions.

Frontiers in Ecology and Evolution↗

USGS2003

Framework for a ground-water quality monitoring and assessment program for California

The State of California uses more ground water than any other State in the Nation. With a population of over 30 million people, an agricultural economy based on intensive irrigation, large urban industrial areas, and naturally elevated concentrations of some trace elements, there is a wide range of contaminant sources that have the potential to contaminate ground water and limit its beneficial uses. In response to the many-and different-potential sources of ground-water contamination, the State of California has evolved an extensive set of rules and programs to protect ground-water quality, and agencies to implement the rules and programs. These programs have in common a focus on compliance with regulations governing chemical use and (or) ground-water quality. Although appropriate for, and successful at, their specific missions, these programs do not at present provide a comprehensive view of ground-water quality in the State of California. In October 2001, The California Assembly passed a bill, AB 599, establishing the Ground-Water- Quality Monitoring Act of 2001.' The goal of AB 599 is to improve Statewide comprehensive ground-water monitoring and increase availability of information about ground-water quality to the public. AB 599 requires the State Water Resources Control Board (SWRCB), in collaboration with an interagency task force (ITF) and a public advisory committee (PAC), to develop a plan for a comprehensive ground-water monitoring program. AB 599 specifies that the comprehensive program should be capable of assessing each ground-water basin in the State through direct and other statistically reliable sampling approaches, and that the program should integrate existing monitoring programs and design new program elements, as necessary. AB 599 also stresses the importance of prioritizing ground-water basins that provide drinking water. The United States Geological Survey (USGS), in cooperation with the SWRCB, and in coordination with the ITF and PAC, has developed a framework for a comprehensive ground-water-quality monitoring and assessment program for California. The proposed framework relies extensively on previous work conducted by the USGS through its National Water-Quality Assessment (NAWQA) program. In particular, the NAWQA program defines three types of ground-water assessment: (1) status, the assessment of the current quality of the ground-water resource; (2) trends, the detection of changes in water quality, and (3) understanding, assessing the human and natural factors that affect ground-water quality. A Statewide, comprehensive ground-water quality-monitoring and assessment program is most efficiently accomplished by applying uniform and consistent study-design and data-collection protocols to the entire State. At the same time, a comprehensive program should be relevant at a variety of scales, and therefore needs to retain flexibility to address regional and local issues. Consequently, many of the program components include a predominant element that will be consistently applied in all basins, and a secondary element that may be applied in specific basins where local conditions warrant attention.

Water-Resources Investigations Report↗

USGS2010

An integrated sampling and analysis approach for improved biodiversity monitoring

Successful biodiversity conservation requires high quality monitoring data and analyses to ensure scientifically defensible policy, legislation, and management. Although monitoring is a critical component in assessing population status and trends, many governmental and non-governmental organizations struggle to develop and implement effective sampling protocols and statistical analyses because of the magnitude and diversity of species in conservation concern. In this article we describe a practical and sophisticated data collection and analysis framework for developing a comprehensive wildlife monitoring program that includes multi-species inventory techniques and community-level hierarchical modeling. Compared to monitoring many species individually, the multi-species approach allows for improved estimates of individual species occurrences, including rare species, and an increased understanding of the aggregated response of a community to landscape and habitat heterogeneity. We demonstrate the benefits and practicality of this approach to address challenges associated with monitoring in the context of US state agencies that are legislatively required to monitor and protect species in greatest conservation need. We believe this approach will be useful to regional, national, and international organizations interested in assessing the status of both common and rare species.

Environmental Management↗

USGS2003

A Framework for Long-term Ecological Monitoring in Olympic National Park: Prototype for the Coniferous Forest Biome

This report is the result of a five-year collaboration between scientists of the U.S. Geological Survey Forest and Rangeland Ecosystem Science Center, Olympic Field Station, and the natural resources staff of Olympic National Park to develop a comprehensive strategy for monitoring natural resources of Olympic National Park. Olympic National Park is the National Park Serviceʼs prototype monitoring park, representing parks in the coniferous forest biome. Under the umbrella of the National Park Serviceʼs prototype parks program, U.S. Geological Survey and Olympic National Park staffs are obligated to: develop strategies and designs for monitoring the long-term health and integrity of national park ecosystems with a significant coniferous forest component. design exportable monitoring protocols that can be used by other parks within the coniferous forest biome (i.e., parks having similar environments), and create a demonstration area and ʻcenter of excellenceʼ for assisting other parks in developing ecological monitoring programs. Olympic National Park is part of the North Coast and Cascades Network, a network of seven Pacific Northwestern park units created recently by the National Park Serviceʼs Inventory and Monitoring Program to extend the monitoring of ʻvital signsʼ of park health to all National Park Service units. It is our intent and hope that the monitoring strategies and conceptual models described here will meet the overall purpose of the prototype parks monitoring program in proving useful not only to Olympic National Park, but also to parks within the North Coast and Cascades Network and elsewhere. Part I contains the conceptual design and sampling framework for the prototype long-term monitoring program in Olympic National Park. In this section, we explore key elements of monitoring design that help to ensure the spatial, ecological, and temporal integration of monitoring program elements and discuss approaches used to design an ecosystem-based monitoring program. Basic monitoring components include ecosystem drivers, (e.g., climate, atmospheric inputs, human pressures), indicators of ecosystem integrity (e.g., biogeochemical indicators), known threats (e.g., impacts of introduced mountain goats), and focal or ʻkeyʼ species (e.g., rare or listed species, Roosevelt elk). Monitoring system drivers and key indicators of ecosystem integrity provide the long-term baseline needed to judge what constitutes ʻunnaturalʼ variation in park resources and provide the earliest possible warning of unacceptable change. Monitoring effects of known threats and the status of focal species will provide information useful to park managers for dealing with current park issues. In Part I we describe the process of identifying potential indicators of ecological condition and present conceptual models of park ecosystems. In addition we report results from several workshops held in conjunction with Olympic National Park aimed at identifying potential indicators of change in the parkʼs ecosystem. First, we describe the responses of Olympic National Park staff to the generic question, “What is the most important resource to monitor in Olympic National Park and why?” followed by the responses from resource and land managers from areas adjoining the park. We also catalogue the responses of various expert groups that we asked to help identify the most appropriate system drivers and indicators of change in the Olympic National Park ecosystems. Results of the workshops provided the justification for selecting basic indicators of ecosystem integrity, effects of current threats to park resources, and focal resources of parks to detect both the currently evident and unforeseeable changes in park resources. We conclude Part I by exploring several generic statistical issues relevant to monitoring natural resources in Olympic National Park. Specifically we discuss trade-offs associated with sampling extensively versus sampling intensively in smaller geographic regions and describe a conceptual framework to guide development of a generic sampling frame for monitoring. We recommend partitioning Olympic National Park into three zones of decreasing accessibility to maximize monitoring efficiency. We present examples of how the generic sampling frame could be used to help ensure spatial integration of individual monitoring projects. Part II of the report is a record of the potential monitoring questions and indicators identified to date in our workshops. The presentation is organized according to the major system drivers, components, and processes identified in the intermediate-level working model of the Olympic National Park ecosystem. For each component of the park system, we develop the need and justification for monitoring, articulate park management issues, and describe key resources and ecosystem functions. We also present a pictorial conceptual model of each ecological subsystem, identify monitoring questions, and list potential indicators for each monitoring question. We conclude each section by identifying linkages of indicators to other ecological subsystems in our general ecosystem model, spatial and temporal contexts for monitoring (where and how often to monitor), and research and development needs. Part II represents the most current detailed listing of potential indicators—the material for subsequent discussions of monitoring priorities and selection of indicators for protocol development. Collectively, the sections of this report contain a comprehensive list of the important monitoring questions and potential indicators as well as recommendations for designing an integrated monitoring program. In Part I, Chapter 6 we provide recommendations on how to proceed with the important next steps in the design process: establishing priorities among the many possible monitoring questions and indicators, and beginning to research and design effective long-term monitoring protocols.

Information and Technology Report↗

USGS2023

Advancing best practices for the analysis of the vulnerability of military installations in the Pacific Basin to coastal flooding under a changing climate – RC-2644

Coastal flooding takes many forms, ranging from major flooding associated with storms to minor flooding associated with exceptionally high tides and other oceanic and atmospheric phenomena on storm-free days. A major societal challenge is to understand and predict how flood magnitude and frequency will manifest at particular places and times, now and in the future. Of particular interest here is how coastal flooding will impact Department of Defense (DoD) installations. In response to this need, this work aims to advance the practical application of statistical and other analytical techniques that can be used to assess the exposure, and ultimately the vulnerability, of built and natural environments to the impacts of coastal flooding. A variety of methods are described and applied to assess exposure. This includes tide gauge station-based diagnosis and prognosis of patterns and trends of Still Water Level, techniques to characterize the expression of ‘lesser extremes’ (e.g., sub-annual to subdecadal event probabilities), and region-wide analysis that improves upon results obtained from conventional single-tide gauge analyses. A novel hybrid statistical and dynamical modeling approach is applied to the analysis of Total Water Levels, necessary for exposure assessment along shorelines exposed to wave action. The hybrid exposure assessment modeling approach is incorporated into a broader mission-based protocol for the assessment of resilience to coastal flooding at the installation level. Demonstrated via an exemplar assessment, which takes into account functional (lost day) as well as financial impacts (lost dollars), the protocol meets the demand for an actionable characterization of how DoD installations will be affected by coastal flooding and improves DoD’s ability to make informed decisions about how to adapt to its effects. The methods described, evaluated, and applied here, including innovative approaches and proof-of-concept products developed through this work, are incorporated into and considered within an analytical framework that serves as guidance as to their relative merits with respect to coastal flood exposure assessment in various circumstances and settings, and illustrates best practices. This will provide engineers, scientists and other practitioners with an enhanced capability to generate information that can be used to support area-wide assessment related to climate adaptation planning and disaster risk reduction as well as site-specific analysis related to design and maintenance of facilities and infrastructure. While the focus is on a select set of DoD sites in the Pacific Basin, the results have broad applicability nationally as well as globally.

Final Report↗

USGS2013

A new map of standardized terrestrial ecosystems of Africa

Terrestrial ecosystems and vegetation of Africa were classified and mapped as part of a larger effort and global protocol (GEOSS – the Global Earth Observation System of Systems), which includes an activity to map terrestrial ecosystems of the earth in a standardized, robust, and practical manner, and at the finest possible spatial resolution. To model the potential distribution of ecosystems, new continental datasets for several key physical environment datalayers (including coastline, landforms, surficial lithology, and bioclimates) were developed at spatial and classification resolutions finer than existing similar datalayers. A hierarchical vegetation classification was developed by African ecosystem scientists and vegetation geographers, who also provided sample locations of the newly classified vegetation units. The vegetation types and ecosystems were then mapped across the continent using a classification and regression tree (CART) inductive model, which predicted the potential distribution of vegetation types from a suite of biophysical environmental attributes including bioclimate region, biogeographic region, surficial lithology, landform, elevation and land cover. Multi-scale ecosystems were classified and mapped in an increasingly detailed hierarchical framework using vegetation-based concepts of class, subclass, formation, division, and macrogroup levels. The finest vegetation units (macrogroups) classified and mapped in this effort are defined using diagnostic plant species and diagnostic growth forms that reflect biogeographic differences in composition and sub-continental to regional differences in mesoclimate, geology, substrates, hydrology, and disturbance regimes (FGDC, 2008). The macrogroups are regarded as meso-scale (100s to 10,000s of hectares) ecosystems. A total of 126 macrogroup types were mapped, each with multiple, repeating occurrences on the landscape. The modeling effort was implemented at a base spatial resolution of 90 m. In addition to creating several rich, new continent-wide biophysical datalayers describing African vegetation and ecosystems, our intention was to explore feasible approaches to rapidly moving this type of standardized, continent-wide, ecosystem classification and mapping effort forward.

African Geographical Review↗

USGS1996

Sampling design for assessing water quality of the Red River of the North basin, Minnesota, North Dakota, and South Dakota, 1993-1995

This map report describes the sampling design for a comprehensive regional assessment of water quality in the Red River of the North Basin, a study unit under the U.S. Geological Survey’s National Water-Quality Assessment Program. The sampling design was developed to address questions about the presence, distribution, and loads of nutrients and pesticides associated with large agricultural regions in the basin and across the Nation. The design also begins to address major local and regional concerns about suspended sediment in surface water and naturally occurring salinity in ground water. Recognizing that the Red River of the North Basin study unit realistically could not be analyzed as a single homogeneous area, a hierarchical sampling stratification for assessing water quality was developed. Landscape features consisting of physiography, soils, land cover and land use, and cropping patterns provided the environmental framework for stratification of streams and surficial aquifers. The environmental framework characterizes the climate and hydrology and relates closely to an ecoregions framework. The environmental and ecoregions frameworks were considered in locating ecological sampling sites. For the subsurface framework, buried sand and gravel aquifers in study unit were subdivided into two general subregions of differing potential saline recharge from underlying bedrock aquifers. Actual sampling sites for streams, aquatic biology, and ground water were described within the proposed sampling stratification. Practical considerations of previously established sampling sites, background information from previous hydrologic investigations, and site suitability for sampling protocols also were considered for final site selection.

Minnesota, North Dakota, South Dakota↗

USGS2019

Population estimates of Antillean manatees in Puerto Rico: An analytical framework for aerial surveys using multi-pass removal sampling

Effective management of the threatened Antillean manatee ( Trichechus manatus manatus ) in Puerto Rico requires reliable estimates of population size. Estimates are needed to assess population responses to management actions, and whether recovery objectives have been met. Aerial surveys have been conducted since 1976, but none adjusted for imperfect detection. We summarize surveys since 1976, report on current distribution, and provide population estimates after accounting for apparent detection probability for surveys between June 2010 and March 2014. Estimates in areas of high concentration (hotspots) averaged 317 ± 101, three times higher than unadjusted counts (104 ± 0.56). Adjusted estimates in three areas outside hotspots also differed markedly from counts (75 ± 9.89 versus 19.5 ± 3.5). Average minimum island-wide estimate was 386 ± 89, similar to the maximum estimate of 360 suggested in 2005, but fewer than the 700 recently suggested by the Puerto Rico Manatee Conservation Center. Manatees were more widespread than previously understood. Improving estimates, locally or island-wide, will require stratifying the island differently and greater knowledge about factors affecting detection probability. Sharing our protocol with partners in nearby islands (e.g., Cuba, Jamaica, Hispaniola), whose populations share genetic make-up, would contribute to enhanced regional conservation through better population estimates and tracking range expansion.

Puerto Rico↗

USGS2019

Monitoring plans for Louisiana’s system-wide assessment and monitoring program (SWAMP). Version IV

The System-Wide Assessment and Monitoring Program (SWAMP) has been envisioned as a long-term monitoring program to ensure a comprehensive network of coastal data collection activities is in place to support the development, implementation, and adaptive management of the coastal protection and restoration program within coastal Louisiana. The Coastwide Reference Monitoring System (CRMS) and Barrier Island Comprehensive Monitoring (BICM) programs have been implemented under SWAMP, while other aspects of system dynamics, including offshore and inland water-body boundary conditions, nontidal freshwater habitats, riverine conditions, risk status, and protection performance, are not presently the subject of CPRA-coordinated (Coastal Protection and Restoration Authority) monitoring. In order to implement these additional aspects of SWAMP, CPRA partnered with The Water Institute of the Gulf and others to develop 1) a programmatic monitoring plan for evaluating the effectiveness of the coastal protection and restoration program on a coastwide scale, and 2) basinwide monitoring plans that will incorporate the elements of the programmatic plan with specific data collection activities designed to capture effects within the basin. Monitoring plans were developed for Barataria Basin, Pontchartrain Region (includes Breton Sound, Pontchartrain and Mississippi River Delta Basins), and the western basins (Calcasieu-Sabine, Mermentau, Teche-Vermilion, Atchafalaya, and Terrebonne) for both the natural and human systems using a process to identify the monitoring variables, objectives, and sampling design. The monitoring variables and objectives identified fall under the general categories of weather and climate, biotic integrity, water quality, hydrology, physical terrain, population and demographics, housing and community characteristics, economy and employment, ecosystem dependency, residential properties protection, and critical infrastructure and essential services protection. A rigorous statistical analysis, examination of modeling needs, and thorough reviews of previous planning and monitoring efforts were conducted to develop the sampling designs for the natural and human system monitoring plans. The plan relies heavily on the use of existing data, thus, coordination with other agencies (e.g., LDEQ , LDWF) and CPRA’s existing monitoring programs (e.g., BICM, CRMS) is critical to the plan’s success. Implementation of the plans will require development of quality control and quality assurance protocols, specific standardized operating procedures for each of the data collection efforts, a data management plan, and a reporting framework to contribute to decision making and reducing uncertainty in management actions.

Louisiana↗

USGS2022

Breeding dynamics of gopher frog metapopulations over 10 years

Populations of amphibians that breed in isolated, ephemeral wetlands may be particularly sensitive to breeding and recruitment rates, which can be influenced by dynamic and difficult-to-predict extrinsic factors. The gopher frog Rana capito is a declining species currently proposed for listing under the U.S. Endangered Species Act, as well as one of many pond-breeding amphibians of conservation concern in the southeastern United States. To represent gopher frog breeding dynamics, we applied an occupancy modeling framework that integrated multiple data sets collected across the species' range to 1) estimate the influence of climate, habitat, and other factors on wetland-specific seasonal breeding probabilities; and 2) use those estimates to characterize seasonal, annual, and regional breeding patterns over a 10-y period. Breeding probability at a wetland was positively influenced by seasonal precipitation (Standardized Precipitation Index) and negatively influenced by fish presence. We found some evidence that the amount of suitable habitat surrounding a wetland was positively correlated with breeding probability during drought conditions. The percentage of sampled wetlands ( N = 192) predicted to have breeding varied seasonally, annually, and regionally across the study. Within-year temporal patterns of breeding differed across the range: in most locations north of Florida, peaks of breeding occurred in winter and spring months; whereas breeding was more dispersed throughout the year in Florida. Peaks of breeding across the 10-y period often occurred during or in the season following high rainfall events (e.g., hurricanes). These results have direct applications for site-level management that aims to increase successful breeding opportunities of gopher frogs and other associated pond-breeding amphibians, including monitoring protocol and intensity, removal of fish, and improving terrestrial habitat conditions surrounding wetlands (e.g., via tree or shrub removal and prescribed fire). The results also have implications for better-informed management through the closer alignment of breeding activity monitoring with predicted seasonal peaks. Furthermore, estimates of breeding frequency can be incorporated into population viability analyses to inform forthcoming assessments of extinction risk and designation of the species' conservation status by the U.S. Fish and Wildlife Service.

Alabama, Florida, Georgia, North Carolina, South C↗

USGS2026

Harmonization of aggregated freshwater biotic data to support continental and global assessment

Biodiversity loss and conservation are increasingly coming into focus in global policy fora, requiring information and assessments at wider spatial and temporal scales than previously considered. However, the monitoring framework required to support such data collection and assessment is lacking in many countries and is not harmonized across countries, hampering these efforts. Aggregation of existing freshwater data offers a solution to the problem of assessing status and trends of ecosystems and biodiversity at large spatial scales in the absence of nationally coordinated monitoring efforts. Analysis of aggregated data from different sources, collected using different protocols and with varying levels of metadata and supporting data, can be challenging and requires decisions regarding data comparability. In this paper, we identify the challenges inherent in harmonizing aggregated freshwater data for analysis, including general concerns related to research goals, spatial and temporal scale, sample selection, sampling effort, and site integrity. We also discuss the challenges related to measured parameters, sampled habitats, sample collection and processing methods, and data integrity for phytoplankton, benthic algae, macrophytes, zooplankton, benthic macroinvertebrates, fish, and supporting variables such as water and sediment chemistry. We provide a workflow to evaluate each of these challenges and make decisions about how best to work with the data. Finally, we review a case study from a large-scale analysis of freshwater data from the circumpolar Arctic region that exemplifies the encountered challenges and the chosen solutions. Through the description of the case study, we provide practical solutions to support aggregation and analysis of existing freshwater data. As global conversations about biodiversity status and trends continue, the demand for large-scale analyses of data from different sources will only grow. In the absence of globally harmonized monitoring, we are faced with the need to ensure comparability of data, making expert judgements where needed to support sound conclusions.

PLOS Water↗