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USGS2025

Environmental drivers of productivity explain population patterns of an Arctic-nesting goose across a half-century

Joint estimation of demographic rates and population size has become an essential tool in ecology because it enables evaluating mechanisms for population change and testing hypotheses about drivers of demography in a single modeling framework. This approach provides a comprehensive perspective on population dynamics and how animal populations will respond to global pressures in future years. However, long-term data for such analyses are often limited in quantity and quality. We developed an integrated population model combining data on demography and population size from nine different sources to understand the population ecology of the lesser snow goose ( Anser caerulescens caerulescens ) in the Pacific Flyway in North America from 1970 to 2022. We divided the flyway population into Wrangel Island and Western Arctic subpopulations and assessed demographic mechanisms for population change and environmental and anthropogenic drivers that influenced demography. During 1970–2022, the estimated spring population of snow geese in the Pacific Flyway increased from ~300,000 to ~2,300,000. Short-term changes in population growth rate were primarily driven by changes in productivity in the Western Arctic and productivity and immigration in Wrangel Island. Changes in hunting and natural mortality had less influence on short-term but likely contributed to the pronounced long-term population growth. Early snowmelt positively influenced per capita productivity in both regions, and warm, rainy weather during the non-breeding season was associated with high per capita productivity in the Western Arctic. In the Western Arctic, per capita productivity was negatively associated with population size, and adult natural mortality was positively associated with population size, indicating density-dependent regulation in this subpopulation. In Wrangel Island, warm weather in early fall decreased juvenile natural mortality. Our results demonstrate that per capita productivity and immigration, rather than adult survival, were the primary mechanisms of short-term population change in this long-lived species. Our results also indicate that environmental conditions and density-dependent effects can impact population dynamics more than harvest, even for a long-lived, commonly harvested species. We demonstrate that a warming climate can have multiple effects on demography, emphasizing the importance of assessing a variety of spatial and temporal factors when predicting how populations might respond to large-scale environmental changes. This emphasizes the importance of conservation plans that consider these environmental drivers, although this may complicate direct management of such populations.

Ecological Applications↗

USGS2010

Facilitation drives 65 years of vegetation change in the Sonoran Desert

Ecological processes of low‐productivity ecosystems have long been considered to be driven by abiotic controls with biotic interactions playing an insignificant role. However, existing studies present conflicting evidence concerning the roles of these factors, in part due to the short temporal extent of most data sets and inability to test indirect effects of environmental variables modulated by biotic interactions. Using structural equation modeling to analyze 65 years of perennial vegetation change in the Sonoran Desert, we found that precipitation had a stronger positive effect on recruitment beneath existing canopies than in open microsites due to reduced evaporation rates. Variation in perennial canopy cover had additional facilitative effects on juvenile recruitment, which was indirectly driven by effects of density and precipitation on cover. Mortality was strongly influenced by competition as indicated by negative density‐dependence, whereas precipitation had no effect. The combined direct, indirect, and interactive facilitative effects of precipitation and cover on recruitment were substantial, as was the effect of competition on mortality, providing strong evidence for dual control of community dynamics by climate and biotic interactions. Through an empirically derived simulation model, we also found that the positive feedback of density on cover produces unique temporal abundance patterns, buffering changes in abundance from high frequency variation in precipitation, amplifying effects of low frequency variation, and decoupling community abundance from precipitation patterns at high abundance. Such dynamics should be generally applicable to low‐productivity systems in which facilitation is important and can only be understood within the context of long‐term variation in climatic patterns. This predictive model can be applied to better manage low‐productivity ecosystems, in which variation in biogeochemical processes and trophic dynamics may be driven by positive density‐dependent feedbacks that influence temporal abundance and productivity patterns.

Ecology↗

USGS2014

Applying threshold concepts to conservation management of dryland ecosystems: Case studies on the Colorado Plateau

Ecosystems may occupy functionally distinct alternative states, some of which are more or less desirable from a management standpoint. Transitions from state to state are usually associated with a particular trigger or sequence of triggers, such as the addition or subtraction of a disturbance. Transitions are often not linear, rather it is common to see an abrupt transition come about even though the trigger increases only incrementally; these are examples of threshold behaviors. An ideal monitoring program, such as the National Park Service’s Inventory and Monitoring Program, would quantify triggers, and be able to inform managers when measurements of a trigger are approaching a threshold so that management action can avoid an unwanted state transition. Unfortunately, both triggers and the threshold points at which state transitions occur are generally only partially known. Using case studies, we advance a general procedure to help identify triggers and estimate where threshold dynamics may occur. Our procedure is as follows: (1) Operationally define the ecosystem type being considered; we suggest that the ecological site concept of the Natural Resource Conservation Service is a useful system, (2) Using all available a priori knowledge to develop a state-and-transition model (STM), which defines possible ecosystem states, plausible transitions among them and likely triggers, (3) Validate the STM by verifying the existence of its states to the greatest degree possible, (4) Use the STM model to identify transitions and triggers likely to be detectable by a monitoring program, and estimate to the greatest degree possible the value of a measurable indicator of a trigger at the point that a state transition is imminent (tipping point), and values that may indicate when management intervention should be considered (assessment points). We illustrate two different methods for attaining these goals using a data-rich case study in Canyonlands National Park, and a data-poor case study in Wupatki National Monument. In the data-rich case, STMs are validated and revised, and tipping and assessment points are estimated using statistical analysis of data. In the data-poor case, we develop an iterative expert opinion survey approach to validate the degree of confidence in an STM, revise the model, identify lack of confidence in specific model components, and create reasonable first approximations of tipping and assessment points, which can later be refined when more data are available. Our goal should be to develop the best set of models possible given the level of information available to support decisions, which is often not much. The approach presented here offers a flexible means of achieving this goal, and determining specific research areas in need of study.

Book chapter↗

USGS2024

A spatiotemporal optimization engine for prescribed burning in the Southeast US

Many ecosystems in the Southeast US are dependent upon frequent low-intensity surface fires to sustain native biodiversity, ecosystem services, and endangered species populations. Today, landscape-scale prescribed fire is required to manage these systems for conservation objectives and to mitigate wildland fire risk. Successful application of prescribed fire in this region requires careful planning and assessment of the risks and tradeoffs involved when deciding whether or not to conduct a burn. Many of these risks are closely tied to ambient environmental conditions and are reflected in sets of ‘prescription’ parameters that define safe and effective operating conditions to meet objectives or regulatory requirements. To facilitate effective decision making and acknowledge growing uncertainties related to climate change effects on wildland fire operations, we developed a spatiotemporal optimization engine to identify near-term optimal burning opportunities for prescribed fire implementation. By mining historical 3-day numerical weather forecasts and observation-based weather data for 2015–2021, we have developed a Bayesian hierarchical model for forecast verification that provides calibrated daily weather forecasts and joint uncertainty estimates on meteorological variables of interest, with the latter serving as a measure of risk associated with prescribed fire activities. Burn allocation decisions are then optimized by considering this risk jointly with the utility of burning a particular habitat parcel. The initial iteration of the optimization engine is demonstrated through a case study of short-term meteorological conditions for the Eglin Air Force Base, located in Florida, USA. Results indicate agreement between the optimization engine and the observed past decision-making, with the largest divergences likely arising primarily from differences between utility functions presumed important and used to develop the optimization engine versus the true utility functions driving management behavior in practice.

Florida↗

USGS2018

Downstream fish passage guide walls: A hydraulic scale model analysis

Partial-depth guide walls are used to improve passage efficiency and reduce the delay of out-migrating anadromous fish species by guiding fish to a bypass route (i.e. weir, pipe, sluice gate) that circumvents the turbine intakes, where survival is usually lower. Evaluation and monitoring studies, however, indicate a high propensity for some fish to pass underneath, rather than along, the guide walls, compromising their effectiveness. In the present study we evaluated a range of guide wall structures to identify where/if the flow field shifts from sweeping (i.e. flow direction primarily along the wall and towards the bypass) to downward-dominant. Many migratory fish species, particularly juveniles, are known to drift with the flow and/or exhibit rheotactic behaviour during their migration. When these behaviours are present, fish follow the path of the flow field. Hence, maintaining a strong sweeping velocity in relation to the downward velocity along a guide wall is essential to successful fish guidance. Nine experiments were conducted to measure the three-dimensional velocity components upstream of a scale model guide wall set at a wide range of depths and angles to flow. Results demonstrated how each guide wall configuration affected the three-dimensional velocity components, and hence the downward and sweeping velocity, along the full length of the guide wall. In general, the velocities produced in the scale model were sweeping dominant near the water surface and either downward dominant or close to the transitional depth near the bottom of the guide wall. The primary exception to this shift from sweeping do downward flow was for the minimum guide wall angle tested in this study (15°). At 15° the flow pattern was fully sweeping dominant for every cross-section, indicating that a guide wall with a relatively small angle may be more likely to produce conditions favorable to efficient guidance. A critical next step is to evaluate the behaviour of migratory fish as they approach and swim along a guide wall in a controlled laboratory environment.

Ecological Engineering↗

USGS2014

Mapping and monitoring Mount Graham red squirrel habitat with Lidar and Landsat imagery

The Mount Graham red squirrel ( Tamiasciurus hudsonicus grahamensis ) is an endemic subspecies located in the Pinaleño Mountains of southeast Arizona. Living in a conifer forest on a sky-island surrounded by desert, the Mount Graham red squirrel is one of the rarest mammals in North America. Over the last two decades, drought, insect infestations, and fire destroyed much of its habitat. A federal recovery team is working on a plan to recover the squirrel and detailed information is necessary on its habitat requirements and population dynamics. Toward that goal I developed and compared three probabilistic models of Mount Graham red squirrel habitat with a geographic information system and logistic regression. Each model contained the same topographic variables (slope, aspect, elevation), but the Landsat model contained a greenness variable (Normalized Difference Vegetation Index) extracted from Landsat, the Lidar model contained three forest-inventory variables extracted from lidar, while the Hybrid model contained Landsat and lidar variables. The Hybrid model produced the best habitat classification accuracy, followed by the Landsat and Lidar models, respectively. Landsat-derived forest greenness was the best predictor of habitat, followed by topographic (elevation, slope, aspect) and lidar (tree height, canopy bulk density, and live basal area) variables, respectively. The Landsat model's probabilities were significantly correlated with all 12 lidar variables, indicating its utility for habitat mapping. While the Hybrid model produced the best classification results, only the Landsat model was suitable for creating a habitat time series or habitat–population function between 1986 and 2013. The techniques I highlight should prove valuable in the development of Landsat- or lidar-based habitat models range wide.

Arizona↗

USGS2008

Soil nutrient-landscape relationships in a lowland tropical rainforest in Panama

Soils play a crucial role in biogeochemical cycles as spatially distributed sources and sinks of nutrients. Any spatial patterns depend on soil forming processes, our understanding of which is still limited, especially in regards to tropical rainforests. The objective of our study was to investigate the effects of landscape properties, with an emphasis on the geometry of the land surface, on the spatial heterogeneity of soil chemical properties, and to test the suitability of soil-landscape modeling as an appropriate technique to predict the spatial variability of exchangeable K and Mg in a humid tropical forest in Panama. We used a design-based, stratified sampling scheme to collect soil samples at 108 sites on Barro Colorado Island, Panama. Stratifying variables are lithology, vegetation and topography. Topographic variables were generated from high-resolution digital elevation models with a grid size of 5 m. We took samples from five depths down to 1 m, and analyzed for total and exchangeable K and Mg. We used simple explorative data analysis techniques to elucidate the importance of lithology for soil total and exchangeable K and Mg. Classification and Regression Trees (CART) were adopted to investigate importance of topography, lithology and vegetation for the spatial distribution of exchangeable K and Mg and with the intention to develop models that regionalize the point observations using digital terrain data as explanatory variables. Our results suggest that topography and vegetation do not control the spatial distribution of the selected soil chemical properties at a landscape scale and lithology is important to some degree. Exchangeable K is distributed equally across the study area indicating that other than landscape processes, e.g. biogeochemical processes, are responsible for its spatial distribution. Lithology contributes to the spatial variation of exchangeable Mg but controlling variables could not be detected. The spatial variation of soil total K and Mg is mainly influenced by lithology. ?? 2007 Elsevier B.V. All rights reserved.

Forest Ecology and Management↗

USGS2018

Landscape-scale variation in canopy water content of giant sequoias during drought

Recent drought (2012–2016) caused unprecedented foliage dieback in giant sequoias ( Sequoiadendron giganteum ), a species endemic to the western slope of the southern Sierra Nevada in central California. As part of an effort to understand and map sequoia response to droughts, we studied the patterns of remotely sensed canopy water content (CWC), both within and among sequoia groves in two successive years during the drought period (2015 and 2016). Our aims were: (1) to quantify giant sequoia responses to severe drought stress at a landscape scale using CWC as an indicator of crown foliage status, and (2) to estimate the effect of environmental correlates that mediate CWC change within and among giant sequoia groves. We utilized airborne high fidelity imaging spectroscopy (HiFIS) and light detection and ranging (LiDAR) data from the Carnegie Airborne Observatory to assess giant sequoia foliage status during 2015 and 2016 of the 2012–2016 droughts. A series of statistical models were generated to classify giant sequoias and to map their location in Sequoia and Kings Canyon National Parks (SEKI) and vicinity. We explored the environmental correlates and the spatial patterns of CWC change at the landscape scale. The mapped CWC was highly variable throughout the landscape during the two observation years, and proved to be most closely related to geological substrates, topography, and site-specific water balance. While there was an overall net gain in sequoia CWC between 2015 and 2016, certain locations (lower elevations, steeper slopes, areas more distant from surface water sources, and areas with greater climate water deficit) showed CWC losses. In addition, we found greater CWC loss in shorter sequoias and those growing in areas with lower sequoia stem densities. Our results suggest that CWC change indicates sequoia response to droughts across landscapes. Long-term monitoring of giant sequoia CWC will likely be useful for modeling and predicting their population-level response to future climate change.

California↗

USGS2009

Assessing the landscape context and conversion risk of protected areas using satellite data products

Since the establishment of the first national park (Yellowstone National Park in 1872) and the first wildlife refuge (Pelican Island in 1903), dramatic changes have occurred in both ecological and cultural landscapes across the U.S. The ability of these protected areas to maintain current levels of biodiversity depend, at least in part, on the integrity of the surrounding landscape. Our objective was to quantify and compare the extent and pattern of natural land cover, risk of conversion, and relationships with demographic and economic variables in counties near National Park Service units and U.S. Fish and Wildlife Service refuges with those counties distant from either type of protected area in the coterminous United States. Our results indicate that landscapes in counties within 10 km of both parks and refuges and those within 10 km of just parks were more natural, more intact, and more protected than those in counties within 10 km of just refuges and counties greater than 10 km from either protected area system. However, they also had greater human population density and change in population, indicating potential conversion risk since the percent of landscape protected averaged < 5% in both groups and human population dynamics are primary drivers of change in many landscapes. Conversion outweighed protection by at least two times (Conservation Risk Index > 2) in 76% of counties near both parks and refuges, 81% of counties near just parks, 91% of counties near just refuges, and 93% of distant counties. Thirteen percent of counties in the coterminous U.S. had moderate to high amounts of natural land cover (> 60%), low protection (< 20%), and the greatest change in population (> 20%). Although these areas are not the most critically endangered, they represent the greatest conservation opportunity, need, and urgency. Our approach is based on national level metrics that are simple, general, informative, and can be understood by broad audiences and by policy makers and managers to assess the health of lands surrounding parks and refuges. Regular monitoring of these metrics with satellite data products in counties surrounding protected areas provides a consistent, national level assessment of management opportunities and potentially adverse changes on adjacent lands.

Remote Sensing of Environment↗

USGS2010

A comprehensive multilocus phylogeny for the wood-warblers and a revised classification of the Parulidae (Aves)

The birds in the family Parulidae-commonly termed the New World warblers or wood-warblers-are a classic model radiation for studies of ecological and behavioral differentiation. Although the monophyly of a 'core' wood-warbler clade is well established, no phylogenetic hypothesis for this group has included a full sampling of wood-warbler species diversity. We used parsimony, maximum likelihood, and Bayesian methods to reconstruct relationships among all genera and nearly all wood-warbler species, based on a matrix of mitochondrial DNA (5840 nucleotides) and nuclear DNA (6 loci, 4602 nucleotides) characters. The resulting phylogenetic hypotheses provide a highly congruent picture of wood-warbler relationships, and indicate that the traditional generic classification of these birds recognizes many non-monophyletic groups. We recommend a revised taxonomy in which each of 14 genera (Seiurus, Helmitheros, Mniotilta, Limnothlypis, Protonotaria, Parkesia, Vermivora, Oreothlypis, Geothlypis, Setophaga, Myioborus, Cardellina, Basileuterus, Myiothlypis) corresponds to a well-supported clade; these nomenclatural changes also involve subsuming a number of well-known, traditional wood-warbler genera (Catharopeza, Dendroica, Ergaticus, Euthlypis, Leucopeza, Oporornis, Parula, Phaeothlypis, Wilsonia). We provide a summary phylogenetic hypothesis that will be broadly applicable to investigations of the historical biogeography, processes of diversification, and evolution of trait variation in this well studied avian group. ?? 2010 Elsevier Inc.

Molecular Phylogenetics and Evolution↗

USGS2013

Winter feeding, growth and condition of brown trout Salmo trutta in a groundwater-dominated stream

Winter can be a stressful period for stream-dwelling salmonid populations, often resulting in reduced growth and survival. Stream water temperatures have been identified as a primary mechanism driving reductions in fitness during winter. However, groundwater inputs can moderate water temperature and may reduce winter severity. Additionally, seasonal reductions in prey availability may contribute to decreased growth and survival, although few studies have examined food webs supporting salmonids under winter conditions. This study employed diet, stable isotope, and mark-recapture techniques to examine winter (November through March) feeding, growth, and condition of brown trout Salmo trutta in a groundwater-dominated stream (Badger Creek, Minnesota, USA). Growth was greater for fish ≤ 150 mm (mean = 4.1 mg g −1 day −1 ) than for those 151–276 mm (mean = 1.0 mg g −1 day −1 ) during the winter season. Overall condition from early winter to late winter did not vary for fish ≤150 mm (mean relative weight (Wr) = 89.5) and increased for those 151–276 mm (mean Wr = 85.8 early and 89.4 late). Although composition varied both temporally and by individual, brown trout diets were dominated by aquatic invertebrates, primarily Amphipods, Dipterans, and Trichopterans. Stable isotope analysis supported the observations of the dominant prey taxa in stomach contents and indicated the winter food web was supported by a combination of allochthonous inputs and aquatic macrophytes. Brown trout in Badger Creek likely benefited from the thermal regime and increased prey abundance present in this groundwater-dominated stream during winter.

Minnesota↗

USGS2024

A protocol for assessing bias and robustness of social network metrics using GPS based radio-telemetry data

Background Social network analysis of animal societies allows scientists to test hypotheses about social evolution, behaviour, and dynamic processes. However, the accuracy of estimated metrics depends on data characteristics like sample proportion, sample size, and frequency. A protocol is urgently needed to assess for bias and robustness of social network metrics estimated for the animal populations especially when a limited number of individuals are monitored. Methods We used GPS telemetry datasets of five ungulate species to combine known social network approaches with novel ones into a comprehensive five-step protocol. To quantify the bias and uncertainty in the network metrics obtained from a partial population, we presented novel statistical methods which are particularly suited for autocorrelated data, such as telemetry relocations. The protocol was validated using a sixth species, the fallow deer, with a known population size where ⇠ 85% of the individuals have been directly monitored. Results Through the protocol, we demonstrated how pre-network data permu tations allow researchers to assess non-random aspects of interactions within a population. The protocol assesses bias in global network metrics, obtains confidence intervals, and quantifies uncertainty of global and node-level network metrics based on the number of nodes in the network. We found that global network metrics like density remained robust even with a lowered sample size, while local network metrics like eigenvector centrality were unreliable for four of the species. The fallow deer network showed low uncertainty and bias even at lower sampling proportions, indicating the importance of a thoroughly sampled population while demonstrating the accuracy of our evaluation methods for smaller samples. Conclusions The protocol allows researchers to analyse GPS-based radio telemetry or other data to determine the reliability of social network metrics. The estimates enable the statistical comparison of networks under di↵erent conditions, such as analysing daily and seasonal changes in the density of a network. The methods can also guide methodological decisions in animal social network research, such as sampling design and allow more accurate ecological inferences from the available data. The R package aniSNA enables researchers to implement this workflow on their dataset, generating reliable inferences and guiding methodological decisions

Article↗

USGS2018

Visual cues for woodpeckers: light reflectance of decayed wood varies by decay fungus

The appearance of wood substrates is likely relevant to bird species with life histories that require regular interactions with wood for food and shelter. Woodpeckers detect decayed wood for cavity placement or foraging, and some species may be capable of detecting trees decayed by specific fungi; however, a mechanism allowing for such specificity remains unidentified. We hypothesized that decay fungi associated with woodpecker cavity sites alter the substrate reflectance in a species-specific manner that is visually discriminable by woodpeckers. We grew 10 species of wood decay fungi from pure cultures on sterile wood substrates of 3 tree species. We then measured the relative reflectance spectra of decayed and control wood wafers and compared them using the receptor noise-limited (RNL) color discrimination model. The RNL model has been used in studies of feather coloration, egg shells, flowers, and fruit to model how the colors of objects appear to birds. Our analyses indicated 6 of 10 decayed substrate/control comparisons were above the threshold of discrimination (i.e., indicating differences discriminable by avian viewers), and 12 of 13 decayed substrate comparisons were also above threshold for a hypothetical woodpecker. We conclude that woodpeckers should be capable of visually detecting decayed wood on trees where bark is absent, and they should also be able to detect visually species-specific differences in wood substrates decayed by fungi used in this study. Our results provide evidence for a visual mechanism by which woodpeckers could identify and select substrates decayed by specific fungi, which has implications for understanding ecologically important woodpecker–fungus interactions.

Wilson Journal of Ornithology↗

USGS2011

Use of the superpopulation approach to estimate breeding population size: An example in asynchronously breeding birds

Many populations of animals are fluid in both space and time, making estimation of numbers difficult. Much attention has been devoted to estimation of bias in detection of animals that are present at the time of survey. However, an equally important problem is estimation of population size when all animals are not present on all survey occasions. Here, we showcase use of the superpopulation approach to capture–recapture modeling for estimating populations where group membership is asynchronous, and where considerable overlap in group membership among sampling occasions may occur. We estimate total population size of long‐legged wading bird (Great Egret and White Ibis) breeding colonies from aerial observations of individually identifiable nests at various times in the nesting season. Initiation and termination of nests were analogous to entry and departure from a population. Estimates using the superpopulation approach were 47–382% larger than peak aerial counts of the same colonies. Our results indicate that the use of the superpopulation approach to model nesting asynchrony provides a considerably less biased and more efficient estimate of nesting activity than traditional methods. We suggest that this approach may also be used to derive population estimates in a variety of situations where group membership is fluid.

Florida↗

USGS1995

Map showing potential metal-mine drainage hazards in Colorado, based on mineral-deposit geology

This map, compiled by the U.S. Geological Survey (USGS) in cooperation with the Colorado Geological Survey (CGS) and the U. S. Bureau of Land Management (BLM), shows potential mine-drainage hazards that may exist in Colorado metal-mining districts, as indicated by the geologic characteristics of the mineral deposits that occur in the respective districts. It was designed to demonstrate how geologic and geochemical information can be used on a regional scale to help assess the potential for mining-related and natural drainage problems in mining districts, unmined mineralized areas, and surrounding watersheds. The map also provides information on the distribution of different mineral deposit types across Colorado. A GIS (Geographic Information System) format was used to integrate geologic, geochemical, water-quality, climate, landuse, and ecological data from diverse sources. Likely mine-drainage signatures were defined for each mining district based on: (1) a review of the geologic characteristics of the mining district, including mineralogy, trace-element content, host-rock lithology, and wallrock alteration, and; (2) results of site specific studies on the geologic controls on mine-drainage composition.

Colorado↗

USGS2017

An introduction to high-frequency nutrient and biogeochemical monitoring for the Sacramento–San Joaquin Delta, northern California

Executive Summary This report is the first in a series of three reports that provide information about high-frequency (HF) nutrient and biogeochemical monitoring in the Sacramento–San Joaquin Delta of northern California (Delta). This first report provides an introduction to the reasons for and fundamental concepts behind collecting HF measurements, and describes the benefits associated with a real-time, continuous, HF, multi-parameter water quality monitoring station network that is co-located with flow stations. It then provides examples of how HF nutrient measurements have improved our understating of nutrient sources and cycling in aquatic systems worldwide, followed by specific examples from the Delta. These examples describe the ways in which HF instrumentation may be used for both fixed-station and spatial assessments. The overall intent of this document is to describe how HF measurements currently (2017) are being used in the Delta to examine the relationship between nutrient concentrations, nutrient cycling, and aquatic habitat conditions. The second report in the series (Downing and others, 2017) summarizes information about HF nutrient and associated biogeochemical monitoring in the northern Delta. The report synthesizes data available from the nutrient and water quality monitoring network currently operated by the U.S. Geological Survey in this ecologically important region of the Delta. In the report, we present and discuss the available data at various timescales—first, at the monthly, seasonal, and inter-annual timescales; and, second, for comparison, at the tidal and event (for example, storms, reservoir releases, phytoplankton blooms) timescales. As expected, we determined that there is substantial variability in nitrate concentrations at short timescales within hours, but also significant variability at longer timescales such as months or years. This multi-scale, high variability affects calculation of fluxes and loads, indicating that HF monitoring is necessary for understanding and assessing flux-based processes and outcomes in tidal environments, such as the Delta. The third report in the series (Bergamaschi and others, 2017) provides information about how to design HF nutrient and biogeochemical monitoring for assessment of nutrient inputs and dynamics in the Delta. The report provides background, principles, and considerations for designing an HF nutrient-monitoring network for the Sacramento–San Joaquin Delta to address high-priority, nutrient-management questions. The report starts with high-priority management questions to be addressed, continues with questions and considerations that place demands and constraints on network design, discusses the principles applicable to network design, and concludes with the presentation of three example nutrient‑monitoring network designs for the Delta. For the three example networks, we assess how they would address high-priority questions identified by the Delta Regional Monitoring Program (Delta Regional Monitoring Program Technical Advisory Committee, 2015).

California↗

USGS2022

Functional wetland loss drives emerging risks to waterbird migration networks

Migratory waterbirds (i.e., shorebirds, wading birds, and waterfowl) rely on a diffuse continental network of wetland habitats to support annual life cycle needs. Emerging threats of climate and land-use change raise new concerns over the sustainability of these habitat networks as water scarcity triggers cascading ecological effects impacting wetland habitat availability. Here we use important waterbird regions in Oregon and California, United States, as a model system to examine patterns of landscape change impacting wetland habitat networks in western North America. Wetland hydrology and flooded agricultural habitats were monitored monthly from 1988 to 2020 using satellite imagery to quantify the timing and duration of inundation—a key delimiter of habitat niche values associated with waterbird use. Trends were binned by management practice and wetland hydroperiods (semi-permanent, seasonal, and temporary) to identify differences in their climate and land-use change sensitivity. Wetland results were assessed using 33 waterbird species to detect non-linear effects of network change across a diversity of life cycle and habitat needs. Pervasive loss of semi-permanent wetlands was an indicator of systemic functional decline. Shortened hydroperiods caused by excessive drying transitioned semi-permanent wetlands to seasonal and temporary hydrologies—a process that in part counterbalanced concurrent seasonal and temporary wetland losses. Expansion of seasonal and temporary wetlands associated with closed-basin lakes offset wetland declines on other public and private lands, including wildlife refuges. Diving ducks, black terns, and grebes exhibited the most significant risk of habitat decline due to semi-permanent wetland loss that overlapped important migration, breeding, molting, and wintering periods. Shorebirds and dabbling ducks were beneficiaries of stable agricultural practices and top-down processes of functional wetland declines that operated collectively to maintain habitat needs. Outcomes from this work provide a novel perspective of wetland ecosystem change affecting waterbirds and their migration networks. Understanding the complexity of these relationships will become increasingly important as water scarcity continues to restructure the timing and availability of wetland resources.

California, Nevada, Oregon↗

USGS2012

Estimating aboveground biomass in interior Alaska with Landsat data and field measurements

Terrestrial plant biomass is a key biophysical parameter required for understanding ecological systems in Alaska. An accurate estimation of biomass at a regional scale provides an important data input for ecological modeling in this region. In this study, we created an aboveground biomass (AGB) map at 30-m resolution for the Yukon Flats ecoregion of interior Alaska using Landsat data and field measurements. Tree, shrub, and herbaceous AGB data in both live and dead forms were collected in summers and autumns of 2009 and 2010. Using the Landsat-derived spectral variables and the field AGB data, we generated a regression model and applied this model to map AGB for the ecoregion. A 3-fold cross-validation indicated that the AGB estimates had a mean absolute error of 21.8 Mg/ha and a mean bias error of 5.2 Mg/ha. Additionally, we validated the mapping results using an airborne lidar dataset acquired for a portion of the ecoregion. We found a significant relationship between the lidar-derived canopy height and the Landsat-derived AGB (R 2 = 0.40). The AGB map showed that 90% of the ecoregion had AGB values ranging from 10 Mg/ha to 134 Mg/ha. Vegetation types and fires were the primary factors controlling the spatial AGB patterns in this ecoregion.

Alaska↗