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At least 37 records · Page 2Linked to original sources
USGS2020

Analyzing vegetation change in a sagebrush ecosystem using long-term field observations and Landsat imagery in Wyoming

The importance of monitoring shrublands to detect and understand changes through time is increasingly recognized as critical to management. This research focuses on ecological change observed over 10 yr of field observation at 126 plots and over 35 yr of the Landsat archive in a shrubland ecosystem. Field data consisting of the fractional cover of shrubs, sagebrush, herbs, litter, and bare ground components were collected to be directly comparable to Landsat time-series predictions at an ecoregion level. We used these data to test three hypotheses. First, that precipitation and temperature govern changes in the proportions of shrubland components on an interannual time scale. Second, that longer-term component change is related to climate change. Finally, that change intensity varies by shrubland communities clustered by biophysical conditions. We found that the field observations and Landsat times-series predictions generally responded similarly to interannual variation in weather, chiefly driven by precipitation. Landsat times-series data provided a reasonable means of scaling up the findings of the field observations to a larger temporal and spatial window. The results of the analysis indicate that shrubland component change intensity significantly varies by biophysical clusters, and indicate a significant increase in the cover of shrubs and sagebrush in long-term monitoring plots between 2008 and 2017 and in the Landsat time-series data across the Wyoming Basin study area from 1985 to 2017 and from 2008 to 2017. Our results indicate that the Landsat time series can be used to answer critical questions regarding the influence of climate change and the suitability of management practices in shrubland ecosystems.

Wyoming↗
USGS2017

Comparison of acoustic recorders and field observers for monitoring tundra bird communities

Acoustic recorders can be useful for studying bird populations but their efficiency and accuracy should be assessed in pertinent ecological settings before use. We investigated the utility of an acoustic recorder for monitoring abundance of tundra‐breeding birds relative to point‐count surveys in northwestern Alaska, USA, during 2014. Our objectives were to 1) compare numbers of birds and species detected by a field observer with those detected simultaneously by an acoustic recorder; 2) evaluate how detection probabilities for the observer and acoustic recorder varied with distance of birds from the survey point; and 3) evaluate whether avian guild‐specific detection rates differed between field observers and acoustic recorders relative to habitat. Compared with the observer, the acoustic recorder detected fewer species (β Method = −0.39 ± 0.07) and fewer individuals (β Method = −0.56 ± 0.05) in total and for 6 avian guilds. Discrepancies were attributed primarily to differences in effective area surveyed (91% missed by device were >100 m), but also to nonvocal birds being missed by the recorder (55% missed <100 m were silent). The observer missed a few individuals and one species detected by the device. Models indicated that relative abundance of various avian guilds was associated primarily with maximum shrub height and less so with shrub cover and visual obstruction. The absence of a significant interaction between survey method (observer vs . acoustic recorder) and any habitat characteristic suggests that traditional point counts and acoustic recorders would yield similar inferences about ecological relationships in tundra ecosystems. Pairing of the 2 methods could increase survey efficiency and allow for validation and archival of survey results.

Alaska↗
USGS2019

An assessment of plant species differences on cellulose oxygen isotopes from two Kenai Peninsula, Alaska peatlands: Implications for hydroclimatic reconstructions

Peat cores are valuable archives of past environmental change because they accumulate plant organic matter over millennia. While studies have primarily focused on physical, ecological, and some biogeochemical proxies, cores from peatlands have increasingly been used to interpret hydroclimatic change using stable isotope analyses of cellulose preserved in plant remains. Previous studies indicate that the stable oxygen isotope compositions (δ 18 O) preserved in alpha cellulose extracted from specific plant macrofossils reflect the δ 18 O values of past peatland water and thereby provide information on long-term changes in hydrology in response to climate. Oxygen isotope analyses of peat cellulose (δ 18 O cellulose ) have been successfully developed from peat cores that accumulate the same species for millennia. However, to fully exploit the potential of this proxy in species-diverse fens, studies are needed that account for the isotopic variations caused by changes in dominant species composition. This study assesses variation in δ 18 O values among peatland plant species and how they relate to environmental waters in two fens informally named Horse Trail and Goldfin, located on the leeward (dry) and windward (wet) side, respectively, of the climatic gradient across the Kenai Peninsula, Alaska. Environmental water δ 18 O values at both fens reflect unmodified δ 18 O values of mean annual precipitation, although at Goldfin standing pools were slightly influenced by evaporation. Modern plant [mosses and Carex spp. (sedges)] δ 18 O cellulose values indicate that all Carex spp. are higher (~2.5‰) than those of mosses, likely driven by their vascular structure and ecophysiological difference from non-vascular mosses. Moss δ 18 O cellulose values within each peatland are similar among the species, and differences appear related to evaporation effects on environmental waters within hummocks and hollows. The plant taxa-environmental water δ 18 O differences are applied to the previously determined Horse Trail Fen untreated bulk δ 18 O record. Results include significant changes to inferred millennial-to-centennial scale hydroclimatic trends where dominant taxa shift from moss to Carex spp., indicating that modern calibration datasets are necessary for interpreting stable isotopes from fens, containing a mix of vascular and nonvascular plants. Accounting for isotopic offsets through macrofossil analysis and modern plant-water isotope measurements opens new opportunities for hydroclimatic reconstructions from fen peatlands.

Alaska↗
USGS2021

Integrating tracking and resight data enables unbiased inferences about migratory connectivity and winter range survival from archival tags

Archival geolocators have transformed the study of small, migratory organisms but analysis of data from these devices requires bias correction because tags are only recovered from individuals that survive and are re-captured at their tagging location. We show that integrating geolocator recovery data and mark–resight data enables unbiased estimates of both migratory connectivity between breeding and nonbreeding populations and region-specific survival probabilities for wintering locations. Using simulations, we first demonstrate that an integrated Bayesian model returns unbiased estimates of transition probabilities between seasonal ranges. We also used simulations to determine how different sampling designs influence the estimability of transition probabilities. We then parameterized the model with tracking data and mark–resight data from declining Painted Bunting ( Passerina ciris ) populations breeding in the eastern United States, hypothesized to be threatened by the illegal pet trade in parts of their Caribbean, nonbreeding range. Consistent with this hypothesis, we found that male buntings wintering in Cuba were 20% less likely to return to the breeding grounds than birds wintering elsewhere in their range. Improving inferences from archival tags through proper data collection and further development of integrated models will advance our understanding of the full annual cycle ecology of migratory species.

Ornithological Applications↗
USGS2017

Large-scale modeled contemporary and future water temperature estimates for 10774 Midwestern U.S. Lakes

Climate change has already influenced lake temperatures globally, but understanding future change is challenging. The response of lakes to changing climate drivers is complex due to the nature of lake-atmosphere coupling, ice cover, and stratification. To better understand the diversity of lake responses to climate change and give managers insight on individual lakes, we modelled daily water temperature profiles for 10,774 lakes in Michigan, Minnesota, and Wisconsin for contemporary (1979–2015) and future (2020–2040 and 2080–2100) time periods with climate models based on the Representative Concentration Pathway 8.5, the worst-case emission scenario. In addition to lake-specific daily simulated temperatures, we derived commonly used, ecologically relevant annual metrics of thermal conditions for each lake. We include all supporting lake-specific model parameters, meteorological drivers, and archived code for the model and derived metric calculations. This unique dataset offers landscape-level insight into the impact of climate change on lakes.

Michigan, Minnesota, Wisconsin↗
USGS2013

Wetland fire scar monitoring and analysis using archival Landsat data for the Everglades

The ability to document the frequency, extent, and severity of fires in wetlands, as well as the dynamics of post-fire wetland land cover, informs fire and wetland science, resource management, and ecosystem protection. Available information on Everglades burn history has been based on field data collection methods that evolved through time and differ by land management unit. Our objectives were to (1) design and test broadly applicable and repeatable metrics of not only fire scar delineation but also post-fire land cover dynamics through exhaustive use of the Landsat satellite data archives, and then (2) explore how those metrics relate to various hydrologic and anthropogenic factors that may influence post-fire land cover dynamics. Visual interpretation of every Landsat scene collected over the study region during the study time frame produced a new, detailed database of burn scars greater than 1.6 ha in size in the Water Conservation Areas and post-fire land cover dynamics for Everglades National Park fires greater than 1.6 ha in area. Median burn areas were compared across several landscape units of the Greater Everglades and found to differ as a function of administrative unit and fire history. Some burned areas transitioned to open water, exhibiting water depths and dynamics that support transition mechanisms proposed in the literature. Classification tree techniques showed that time to green-up and return to pre-burn character were largely explained by fire management practices and hydrology. Broadly applicable as they use data from the global, nearly 30-year-old Landsat archive, these methods for documenting wetland burn extent and post-fire land cover change enable cost-effective collection of new data on wetland fire ecology and independent assessment of fire management practice effectiveness.

Florida↗
USGS2011

Guidelines for collecting and maintaining archives for genetic monitoring

Rapid advances in molecular genetic techniques and the statistical analysis of genetic data have revolutionized the way that populations of animals, plants and microorganisms can be monitored. Genetic monitoring is the practice of using molecular genetic markers to track changes in the abundance, diversity or distribution of populations, species or ecosystems over time, and to follow adaptive and non-adaptive genetic responses to changing external conditions. In recent years, genetic monitoring has become a valuable tool in conservation management of biological diversity and ecological analysis, helping to illuminate and define cryptic and poorly understood species and populations. Many of the detected biodiversity declines, changes in distribution and hybridization events have helped to drive changes in policy and management. Because a time series of samples is necessary to detect trends of change in genetic diversity and species composition, archiving is a critical component of genetic monitoring. Here we discuss the collection, development, maintenance, and use of archives for genetic monitoring. This includes an overview of the genetic markers that facilitate effective monitoring, describes how tissue and DNA can be stored, and provides guidelines for proper practice.

Conservation Genetics Resources↗
USGS2025

Ecological factors decouple Great Lakes fish mercury concentrations trends decadal declines in mercury emissions

Atmospheric mercury (Hg) deposition has been declining in North America but remains the dominant delivery mechanism to the Great Lakes. The Lakes are highly efficient at bioaccumulating methylmercury, making the fish excellent sentinels for tracking shifts in atmospheric Hg deposition. Invasive mussels have altered biogeochemical processes, prey populations and fish dietary strategies asynchronously and to varied extents across the lower four lakes, impacting fish Hg exposure. To test if fish are adapting to new biogeochemical conditions, we analyzed a 40 year fish archive for carbon and nitrogen isotope ratios and amino acid-specific nitrogen isotope ratios. To assess Hg sources, we measured Hg isotope ratios. We reconstructed and compared energetic pathways that impact fish Hg concentrations to Hg-source trends. We found fish-Hg concentrations are declining but not monotonically due to ecological disturbances. Fish-Hg isotope values, unimpacted by ecological disturbance, confirm that sources of bioaccumulated Hg shift contemporaneously with changes in atmospheric Hg concentrations. Across Lakes, the degree of responsiveness to changes in atmospheric Hg concentrations mirrors the proportion of atmospheric-delivered Hg we previously modeled. Changes in both fish concentrations and fish isotope values outpace paleolimnetic reconstructions suggesting declines in atmospheric Hg concentrations impact fish Hg more than sediment.

Great Lakes↗
USGS2005

Remote sensing sensitivity to fire severity and fire recovery

The paper examines fundamental ways that geospatial data on fire severity and recovery are influenced by conditions of the remote sensing. Remote sensing sensitivities are spatial, temporal and radiometric in origin. Those discussed include spatial resolution, the sampling time of year, and time since fire. For standard reference, sensitivities are demonstrated with examples drawn from an archive of burn assessments based on one radiometric index, the differenced Normalized Burn Ratio. Resolution determines the aggregation of fire effects within a pixel ( alpha variation ), hence defining the detected ecological response, and controlling the ability to determine patchiness and spatial distribution of responses throughout a burn ( beta variation ). As resolution decreases, alpha variation increases, extracting beta variation from the complexity of the whole burn. Seasonal timing impacts the radiometric quality of data in terms of transmittance, sun angle, and potential for enhanced contrast between responses within burns. Remote sensing sensitivity can degrade during many fire seasons when snow, incomplete burning, hazy conditions, low sun angles, or extended drought are common. Time since fire ( lag timing ) most notably shapes severity detection through the first-order fire effects evident in survivorship and delayed mortality that emerge by the growth period after fire. The former effects appear overly severe at first, but diminish, as burned vegetation remains viable. Conversely, the latter signals vegetation that appears healthy at first, but is damaged by heat to the extent that it soon dies. Both responses can lead to either over- or under-estimating severity, respectively, depending on fire behavior and pre-fire composition unique to each burned area. Based on implications of such sensitivities, three sampling intervals for short-term burn severity are identified; rapid , initial , and extended assessment , sampled within ca. two weeks, two months, and depending on the ecotype, from three months to one year after fire, respectively. Jointly, remote sensing conditions and the way burns are studied yield different tendencies for data quality and information content that impact the objectives and hypotheses that can be studied. Such considerations can be commonly overlooked, but need to be incorporated especially in comparative studies, and to build long-term reference databases on fire severity and recovery.

Conference Paper↗
USGS2018

Distribution and foraging patterns of common loons on Lake Michigan with implications for exposure to type E avian botulism

Common loons ( Gavia immer ) staging on the Great Lakes during fall migration are at risk to episodic outbreaks of type E botulism. Information on distribution, foraging patterns, and exposure routes of loons are needed for understanding the physical and ecological factors that contribute to avian botulism outbreaks. Aerial surveys were conducted to document the spatiotemporal distribution of common loons on Lake Michigan during falls 2011–2013. In addition, satellite telemetry and archival geolocator tags were used to determine the distribution and foraging patterns of individual common loons while using Lake Michigan during fall migration. Common loon distribution observed during aerial surveys and movements of individual radiomarked and/or geotagged loons suggest a seasonal pattern of use, with early fall use of Green Bay and northern Lake Michigan followed by a shift in distribution to southern Lake Michigan before moving on to wintering areas. Common loons tended to occupy offshore areas of Lake Michigan and, on average, spent the majority of daylight hours foraging. Dive depths were as deep as 60 m and dive characteristics suggested that loons were primarily foraging on benthic prey. A recent study concluded that round gobies ( Neogobius melanostomus ) are an important prey item of common loons and may be involved in transmission of botulinum neurotoxin type E. Loon distribution coincides with the distribution of dreissenid mussel biomass, an important food resource for round gobies. Our observations support speculation that energy transfer to higher trophic levels via gobies may occur in deep-water habitats, along with transfer of botulinum neurotoxin.

Michigan, Minnesota, Wisconsin↗
USGS2018

Climate-related variation in plant peak biomass and growth phenology across Pacific Northwest tidal marshes

The interannual variability of tidal marsh plant phenology is largely unknown and may have important ecological consequences. Marsh plants are critical to the biogeomorphic feedback processes that build estuarine soils, maintain marsh elevation relative to sea level, and sequester carbon. We calculated Tasseled Cap Greenness, a metric of plant biomass, using remotely sensed data available in the Landsat archive to assess how recent climate variation has affected biomass production and plant phenology across three maritime tidal marshes in the Pacific Northwest of the United States. First, we used clipped vegetation plots at one of our sites to confirm that tasseled cap greenness provided a useful measure of aboveground biomass (r 2 = 0.72). We then used multiple measures of biomass each growing season over 20–25 years per study site and developed models to test how peak biomass and the date of peak biomass varied with 94 climate and sea-level metrics using generalized linear models and Akaike Information Criterion (AIC) model selection. Peak biomass was positively related to total annual precipitation, while the best predictor for date of peak biomass was average growing season temperature, with the peak 7.2 days earlier per degree C. Our study provides insight into how plants in maritime tidal marshes respond to interannual climate variation and demonstrates the utility of time-series remote sensing data to assess ecological responses to climate stressors.

Oregon, Washington↗
USGS2008

Modeling and dynamic monitoring of ecosystem performance in the Yukon River Basin

Central Alaska is ecologically sensitive and experiencing stress in response to marked regional warming. Resource managers would benefit from an improved ability to monitor ecosystem processes in response to climate change, fire, insect damage, and management policies and to predict responses to future climate scenarios. We have developed a method for analyzing ecosystem performance as represented by the growing season integral of normalized difference vegetation index (NDVI), which is a measure of greenness that can be interpreted in terms of plant growth or photosynthetic activity (gross primary productivity). The approach illustrates the status and trends of ecosystem changes and separates the influences of climate and local site conditions from the influences of disturbances and land management. We emphasize the ability to quantify ecosystem processes, not simply changes in land cover, across the entire period of the remote sensing archive (Wylie and others, 2008). The method builds upon remotely sensed measures of vegetation greenness for each growing season. By itself, however, a time series of greenness often reflects annual climate variations in temperature and precipitation. Our method seeks to remove the influence of climate so that changes in underlying ecological conditions are identified and quantified. We define an "expected ecosystem performance" to represent the greenness response expected in a particular year given the climate of that year. We distinguish "performance anomalies" as cases where the ecosystem response is significantly different from the expected ecosystem performance. Maps of the performance anomalies (fig. 1) and trends in the anomalies give valuable information on the ecosystems for land managers and policy makers at a resolution of 1 km to 250 m.

Fact Sheet↗
USGS2025

Designs for cyanobacterial harmful algal bloom monitoring in the Sacramento–San Joaquin Delta, California

Cyanobacterial harmful algal blooms (CHABs) are a growing concern in freshwater environments. These blooms can lead to degraded water quality, ecosystem disruptions, and public health threats due to the production of potent cyanotoxins. The Sacramento–San Joaquin Delta (California, USA; the Delta) has experienced CHABs since 1999, including CHABs that produce cyanotoxins at concentrations exceeding recreational advisory threshold levels. In response to the CHAB monitoring needs in the Delta, in 2024 a CHAB monitoring strategy for the Sacramento–San Joaquin Delta was released. The CHAB monitoring strategy recommended implementing a comprehensive monitoring program aligned with regional priorities, and this report responds directly to that recommendation. Building on the CHAB monitoring strategy, it describes three example monitoring designs that draw from past studies to address present needs. To develop designs, the report outlines key components and considerations for implementing a CHAB monitoring program in the Delta. It provides: background on monitoring and modeling approaches, an overview of current monitoring programs in the region, guidance for selecting monitoring locations, indicators, and sampling frequencies, and example designs to guide program planning and budgeting. The overarching goal of the report is to help agencies and stakeholders move from high-level recommendations to practical, actionable designs that are tailored to the Delta’s physical, anthropogenic, and ecological landscape.

ESS Open Archive↗
USGS2021

Comparison of historical water temperature measurements with landsat analysis ready data provisional surface temperature estimates for the Yukon River in Alaska

Water temperature is a key element of freshwater ecological systems and a critical element within natural resource monitoring programs. In the absence of in situ measurements, remote sensing platforms can indirectly measure water temperature over time and space. The Earth Resources Observation and Science (EROS) Center has processed archived Landsat imagery into analysis ready data (ARD), including Level-2 Provisional Surface Temperature (pST) estimates derived from the Landsat 4–5 Thematic Mapper (TM), Landsat 7 Enhanced Thematic Mapper Plus (ETM+), and Landsat 8 Thermal Infrared Sensor (TIRS). We compared in situ measurements of water temperature within the Yukon River in Alaska with 52 instances of pST estimates between June 2014 and September 2020. Agreement was good with an RMSE of 2.25 °C and only a slight negative bias in the estimated mean daily water temperature of −0.47 °C. For the 52 dates compared, the average daily water temperature measured by the USGS streamgage was 11.3 °C with a standard deviation of 5.7 °C. The average daily pST estimate was 10.8 °C with a standard deviation of 6.1 °C. At least in the case of large unstratified rivers in Alaska, ARD pST can be used to infer water temperature in the absence of or in tandem with ground-based water temperature monitoring campaigns.

Alaska↗
USGS2014

Remote sensing of land surface phenology

Remote sensing of land-surface phenology is an important method for studying the patterns of plant and animal growth cycles. Phenological events are sensitive to climate variation; therefore phenology data provide important baseline information documenting trends in ecology and detecting the impacts of climate change on multiple scales. The USGS Remote sensing of land surface phenology program produces annually, nine phenology indicator variables at 250 m and 1,000 m resolution for the contiguous U.S. The 12 year archive is available at http://phenology.cr.usgs.gov/index.php .

Fact Sheet↗
USGS2012

Laboratory toxicity and benthic invertebrate field colonization of Upper Columbia River sediments: Finding adverse effects using multiple lines of evidence

From 1930 to 1995, the Upper Columbia River (UCR) of northeast Washington State received approximately 12 million metric tons of smelter slag and associated effluents from a large smelter facility located in Trail, British Columbia, approximately 10 km north of the United States–Canadian border. Studies conducted during the past two decades have demonstrated the presence of toxic concentrations of heavy metals in slag-based sandy sediments, including cadmium, copper, zinc, and lead in the UCR area as well as the downstream reservoir portion of Lake Roosevelt. We conducted standardized whole-sediment toxicity tests with the amphipod Hyalella azteca (28-day) and the midge Chironomus dilutus (10-day) on 11 samples, including both UCR and study-specific reference sediments. Metal concentrations in sediments were modeled for potential toxicity using three approaches: (1) probable effects quotients (PEQs) based on total recoverable metals (TRMs) and simultaneously extracted metals (SEMs); (2) SEMs corrected for acid-volatile sulfides (AVS; i.e., ∑SEM − AVS); and (3) ∑SEM − AVS normalized to the fractional organic carbon (f oc ) (i.e., ∑SEM − AVS/f oc ). The most highly metal-contaminated sample (∑PEQ TRM = 132; ∑PEQ SEM = 54; ∑SEM − AVS = 323; and ∑SEM − AVS/ foc = 64,600 umol/g) from the UCR was dominated by weathered slag sediment particles and resulted in 80% mortality and 94% decrease in biomass of amphipods; in addition, this sample significantly decreased growth of midge by 10%. The traditional ∑AVS – SEM, uncorrected for organic carbon, was the most accurate approach for estimating the effects of metals in the UCR. Treatment of the toxic slag sediment with 20% Resinex SIR-300 metal-chelating resin significantly decreased the toxicity of the sample. Samples ∑SEM − AVS > 244 was not toxic to amphipods or midge in laboratory testing, indicating that this value may be an approximate threshold for effects in the UCR. In situ benthic invertebrate colonization studies in an experimental pond (8-week duration) indicated that two of the most metal-contaminated UCR sediments (dominated by high levels of sand-sized slag particles) exhibited decreased invertebrate colonization compared with sand-based reference sediments. Field-exposed SIR-300 resin samples also exhibited decreased invertebrate colonization numbers compared with reference materials, which may indicate behavioral avoidance of this material under field conditions. Multiple lines of evidence (analytical chemistry, laboratory toxicity, and field colonization results), along with findings from previous studies, indicate that high metal concentrations associated with slag-enriched sediments in the UCR are likely to adversely impact the growth and survival of native benthic invertebrate communities. Additional laboratory toxicity testing, refinement of the applications of sediment benchmarks for metal toxicity, and in situ benthic invertebrate studies will assist in better defining the spatial extent, temporal variations, and ecological impacts of metal-contaminated sediments in the UCR system.

Trail↗
USGS2017

Basis function models for animal movement

Advances in satellite-based data collection techniques have served as a catalyst for new statistical methodology to analyze these data. In wildlife ecological studies, satellite-based data and methodology have provided a wealth of information about animal space use and the investigation of individual-based animal–environment relationships. With the technology for data collection improving dramatically over time, we are left with massive archives of historical animal telemetry data of varying quality. While many contemporary statistical approaches for inferring movement behavior are specified in discrete time, we develop a flexible continuous-time stochastic integral equation framework that is amenable to reduced-rank second-order covariance parameterizations. We demonstrate how the associated first-order basis functions can be constructed to mimic behavioral characteristics in realistic trajectory processes using telemetry data from mule deer and mountain lion individuals in western North America. Our approach is parallelizable and provides inference for heterogenous trajectories using nonstationary spatial modeling techniques that are feasible for large telemetry datasets. Supplementary materials for this article are available online.

Journal of the American Statistical Association↗
USGS2020

Ecological insights from three decades of animal movement tracking across a changing Arctic

The Arctic is entering a new ecological state, with alarming consequences for humanity. Animal-borne sensors offer a window into these changes. Although substantial animal tracking data from the Arctic and subarctic exist, most are difficult to discover and access. Here, we present the new Arctic Animal Movement Archive (AAMA), a growing collection of more than 200 standardized terrestrial and marine animal tracking studies from 1991 to the present. The AAMA supports public data discovery, preserves fundamental baseline data for the future, and facilitates efficient, collaborative data analysis. With AAMA-based case studies, we document climatic influences on the migration phenology of eagles, geographic differences in the adaptive response of caribou reproductive phenology to climate change, and species-specific changes in terrestrial mammal movement rates in response to increasing temperature.

Science↗