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USGS2025

A spatiotemporal deep learning approach for predicting daily air-water temperature signal coupling and identification of key watershed physical parameters in a montane watershed

Seasonal shifts from runoff to groundwater dominance influence daily headwater stream temperatures, especially where local groundwater input is strong. This input buffers temperature during hot periods, supporting cold-water habitats. Recent studies use air–water temperature signal metrics to identify zones of strong stream–groundwater connectivity. While Previous studies used air–water signal ratios as proxies for groundwater influence but were limited to specific sites and periods, without dynamic forecasting. This study is the first to forecast daily A r as a spatiotemporal signal using a Graph Convolutional Network–Long Short-Term Memory (GCN-LSTM) model. The model was trained using hydroclimate data (air temperature, precipitation, shortwave radiation, streamflow) and watershed physical features (e.g., sand content, slope). Results showed high predictive skill, achieving R 2 (NSE, RMSE) of 0.86 (0.73, 0.0004) for one-day-ahead to 0.52 (0.50, 0.0009) for seven-days ahead forecasts. Prior studies often have not explicitly incorporated spatial hydrogeologic drivers, but this model explicitly incorporates them to assess their impact on A r forecasting and stream-groundwater connectivity. Feature analysis identified mean sand, elevation, slope, clay, and TWI as key predictors of A r . Stronger groundwater signals appeared in hillslopes, elevations, and tributaries, highlighting watershed influence on streamflow. However, limitations include reliance on historical air–water temperature patterns for training and limited representation of extreme climate conditions. Despite these limitations, unlike previous studies relying on measured in-situ stream and air temperature, this study forecasts A r directly from climate and physiographic features after training, avoiding in-situ data requirements. Findings aiding predictions of stream ecosystem resilience.

New York↗

USGS2010

Large-scale coastal change in the Columbia River littoral cell: an overview

This overview introduces large-scale coastal change in the Columbia River littoral cell (CRLC). Covering 165 km of the southwest Washington and northwest Oregon coasts, the littoral cell is made up of wide low-sloping dissipative beaches, broad coastal dunes and barrier plains, three large estuaries, and is bounded by rocky headlands. The beaches and inner shelf are composed of fine-grained sand from the Columbia River and are exposed to a high-energy winter wave climate. Throughout the Holocene, the CRLC has undergone large fluctuations in shoreline change trends, responding to a variety of coastal change drivers, including changing rates of sea-level rise, infrequent, yet catastrophic, co-seismic subsidence events, a large regional sediment supply, inter-annual climatic fluctuations (El Niño cycles), seasonally varying wave climate, and numerous anthropogenic influences. Human influences on the CRLC include construction of over 200 dams in the Columbia River drainage basin, dredging of navigation channels removing sand to upland sites and offshore deep-water sites, and construction of large inlet jetties at the entrances to the Columbia River and Grays Harbor. The construction of these massive entrance jetties at the end of the 19th century has been the dominant driver of coastal change through most of the littoral cell over the last hundred years. Presently, some beaches in the littoral cell are eroding in response to nearshore sediment deficits resulting from a) ebb-jets of the confined entrances pushing the previously large, shallow ebb-tidal deltas offshore into deeper water, and b) waves dispersing the nearshore delta flanks initially onshore and then alongshore away from the jetties. This overview describes 1) the motivation for developing a system-wide understanding of sediment dynamics in the littoral cell at multiple time and space scales, 2) the formation and approach of the Southwest Washington Coastal Erosion Study, and 3) an introduction to the papers in this special issue.

Washington;Oregon↗

USGS2007

Dynamics of cover, UV-protective pigments, and quantum yield in biological soil crust communities of an undisturbed Mojave Desert shrubland

Biological soil crusts are an integral part of dryland ecosystems. We monitored the cover of lichens and mosses, cyanobacterial biomass, concentrations of UV-protective pigments in both free-living and lichenized cyanobacteria, and quantum yield in the soil lichen species Collema in an undisturbed Mojave Desert shrubland. During our sampling time, the site received historically high and low levels of precipitation, whereas temperatures were close to normal. Lichen cover, dominated by Collema tenax and C. coccophorum , and moss cover, dominated by Syntrichia caninervis , responded to both increases and decreases in precipitation. This finding for Collema spp. at a hot Mojave Desert site is in contrast to a similar study conducted at a cool desert site on the Colorado Plateau in SE Utah, USA, where Collema spp. cover dropped in response to elevated temperatures, but did not respond to changes in rainfall. The concentrations of UV-protective pigments in free-living cyanobacteria at the Mojave Desert site were also strongly and positively related to rainfall received between sampling times ( R 2 values ranged from 0.78 to 0.99). However, pigment levels in the lichenized cyanobacteria showed little correlation with rainfall. Quantum yield in Collema spp. was closely correlated with rainfall. Climate models in this region predict a 3.5–4.0 °C rise in temperature and a 15–20% decline in winter precipitation by 2099. Based on our data, this rise in temperature is unlikely to have a strong effect on the dominant species of the soil crusts. However, the predicted drop in precipitation will likely lead to a decrease in soil lichen and moss cover, and high stress or mortality in soil cyanobacteria as levels of UV-protective pigments decline. In addition, surface-disturbing activities (e.g., recreation, military activities, fire) are rapidly increasing in the Mojave Desert, and these disturbances quickly remove soil lichens and mosses. These stresses combined are likely to lead to shifts in species composition and the local extirpation of some lichen or moss species. As these organisms are critical components of nutrient cycling, soil fertility, and soil stability, such changes are likely to reverberate throughout these ecosystems.

Mojave Desert↗

USGS2008

The Effects of the Saluda Dam on the Surface-Water and Ground-Water Hydrology of the Congaree National Park Flood Plain, South Carolina

The Congaree National Park was established '... to preserve and protect for the education, inspiration, and enjoyment of present and future generations an outstanding example of a near-virgin, southern hardwood forest situated in the Congaree River flood plain in Richland County, South Carolina' (Public Law 94-545). The resource managers at Congaree National Park are concerned about the timing, frequency, magnitude, and duration of flood-plain inundation of the Congaree River. The dynamics of the Congaree River directly affect ground-water levels in the flood plain, and the delivery of sediments and nutrients is constrained by the duration, extent, and frequency of flooding from the Congaree River. The Congaree River is the southern boundary of the Congaree National Park and is formed by the convergence of the Saluda and Broad Rivers 24 river miles upstream from the park. The streamflow of the Saluda River has been regulated since 1929 by the operation of the Saluda Dam at Lake Murray. The U.S. Geological Survey, in cooperation with the National Park Service, Congaree National Park, studied the interaction between surface water in the Congaree River and ground water in the flood plain to determine the effect Saluda Dam operations have on water levels in the Congaree National Park flood plain. Analysis of peak flows showed the reduction in peak flows after the construction of Lake Murray was more a result of climate variability and the absence of large floods after 1930 than the operation of the Lake Murray dam. Dam operations reduced the recurrence interval of the 2-year to 100-year peak flows by 6.1 to 17.6 percent, respectively. Analysis of the daily gage height of the Congaree River showed that the dam has had the effect of lowering high gage heights (95th percentile) in the first half of the year (December to May) and raising low gage heights (5th percentile) in the second half of the year (June to November). The dam has also had the effect of increasing the 1-, 3-, 7-, 30-, and 90-day minimum gage heights by as much as 23.9 percent and decreasing the 1-, 3-, 7-, 30-, and 90-day maximum gage heights by as much as 7.2 percent. Analysis of the ground-water elevations in the Congaree National Park flood plain shows similar results as the gage-height analysis--the dam has had the effect of lowering high ground-water elevations and increasing low ground-water elevations. Overall, the operation of the dam has had a greater effect on the gage heights within the river banks than gage heights in the flood plain. This result may have a greater effect on the subsurface water levels of the surficial flood-plain aquifer than the frequency and magnitude of inundation of the flood plain.

South Carolina↗

USGS2021

Lake Ontario cisco population dynamics based on long-term surveys

Prior to European settlement, cisco (Coregonus artedi) were likely one of Lake Ontario’s most abundant fishes but currently represent a small portion of the fish community. To understand how the population has changed over the past 70 years we compared trends in annual catch rates from gillnet and bottom trawl surveys and commercial fishery landings. In surveys, cisco were generally rare, and represented 0.2, 0.4, and 0.001% of all fish caught in two gillnet surveys and bottom trawl surveys. Cisco catch rates in gillnets and trawls were positively correlated and correlations increased when gillnet catches two years later were compared to trawls since trawls tended to capture smaller, juvenile-sized cisco relative to gillnets. Survey catch rates suggest recruitment is generally low, but discrete periods of relatively greater recruitment in the 1980s and mid-2010s suggest reproductive conditions for cisco vary temporally. Trawl surveys were the most spatially extensive survey and illustrated catch rates were highest in northeastern Lake Ontario. Greater cisco abundance in this region may be related to more-abundant embayment spawning habitat, greater distance from winter aggregations of nonnative planktivores, or more appropriate environmental conditions during spawing. At the basin scale, Lake Ontario bottom trawl catch per unit effort (CPUE) was positively correlated to Lake Superior trawl CPUE suggesting a regional driver, such as climate, may be similarly impacting both populations. Concurrent patterns across Lake Ontario surveys support the idea that cisco are currently a small portion of the fish community, recruitment remains inconsistent, and habitats in northeastern Lake Ontario appear critical to the remnant populations.

Lake Ontario↗

USGS2016

Static and dynamic controls on fire activity at moderate spatial and temporal scales in the Alaskan boreal forest

Wildfire, a dominant disturbance in boreal forests, is highly variable in occurrence and behavior at multiple spatiotemporal scales. New data sets provide more detailed spatial and temporal observations of active fires and the post-burn environment in Alaska. In this study, we employ some of these new data to analyze variations in fire activity by developing three explanatory models to examine the occurrence of (1) seasonal periods of elevated fire activity using the number of MODIS active fire detections data set (MCD14DL) within an 11-day moving window, (2) unburned patches within a burned area using the Monitoring Trends in Burn Severity fire severity product, and (3) short-to-moderate interval (<60 yr) fires using areas of burned area overlap in the Alaska Large Fire Database. Explanatory variables for these three models included dynamic variables that can change over the course of the fire season, such as weather and burn date, as well as static variables that remain constant over a fire season, such as topography, drainage, vegetation cover, and fire history. We found that seasonal periods of high fire activity are associated with both seasonal timing and aggregated weather conditions, as well as the landscape composition of areas that are burning. Important static inputs to the model of seasonal fire activity indicate that when fire weather conditions are suitable, areas that typically resist fire (e.g., deciduous stands) may become more vulnerable to burning and therefore less effective as fire breaks. The occurrence of short-to-moderate interval fires appears to be primarily driven by weather conditions, as these were the only relevant explanatory variables in the model. The unique importance of weather in explaining short-to-moderate interval fires implies that fire return intervals (FRIs) will be sensitive to projected climate changes in the region. Unburned patches occur most often in younger stands, which may be related to a greater deciduous fraction of vegetation as well as lower fuel loads compared with mature stands. The fraction of unburned patches may therefore increase in response to decreasing FRIs and increased deciduousness in the region, or these may decrease if fire weather conditions become more severe.

Alaska↗

USGS2016

Evaluating potential sources of variation in Chironomidae catch rates on sticky traps

Sticky traps are a convenient tool for assessing adult aquatic insect population dynamics, but there are many practical questions about how trap sampling artefacts may affect observed results. Utilising study sites on the Colorado River and two smaller streams in northern Arizona, USA, we evaluated whether catch rates and sex ratios of Chironomidae, a ubiquitous aquatic insect, were affected by spraying traps with insecticide, placing traps at different heights above ground, and placing traps at different locations within a terrestrial habitat patch. We also evaluated temporal variation in Chironomidae counts monthly over a 9-month growing season. We found no significant variation in catch rates or sex ratios between traps treated versus untreated with insecticide, nor between traps placed at the upstream or downstream end of a terrestrial habitat patch. Traps placed near ground level did have significantly higher catch rates than traps placed at 1.5 m, although sex ratios were similar across heights. Chironomidae abundance and sex ratios also varied from month-to-month and seemed to be related to climatic conditions. Our results inform future sticky trap studies by demonstrating that trap height, but not insecticide treatment or precise trap placement within a habitat patch, is an important source of variation influencing catch rates.

Arizona↗

USGS2023

Sediment sources and connectivity linked to hydrologic pathways and geomorphic processes: A conceptual model to specify sediment sources and pathways through space and time

Sediment connectivity is a conceptualization for the transfer and storage of sediment among different geomorphic compartments across upland landscapes and channel networks. Sediment connectivity and dysconnectivity are linked to the water cycle and hydrologic systems with the associated multiscale interactions with climate, soil, topography, ecology, and landuse/landcover under natural variability and human intervention. We review current sediment connectivity and modeling approaches evaluating and quantifying water and sediment transfer in catchment systems. Many studies highlight the interaction between sediment and water in defining landscape connectivity, but many efforts to quantify and/or simulate sediment connectivity rely on the topographic/structural controls on sediment erosion and delivery. More recent modeling efforts integrate functional and structural connectivity to capture hydrologic properties influencing sediment delivery. Though the recent modeling development is encouraging, a comprehensive sediment connectivity framework, which integrates geomorphic and hydrologic processes across spatiotemporal scales, has not yet been accomplished. Such an effort requires understanding the hydrologic and geomorphic processes that control sediment source, storage, and transport at different spatiotemporal scales and across various geophysical conditions. We propose a path for developing this new understanding through an integrated hydrologic and sediment connectivity conceptual model that broadly categorizes dominant processes and patterns relevant to understanding sediment flux dynamics. The conceptual model describes hydrologic–sediment connectivity regimes through spatial-temporal feedback between hydrologic processes and geomorphic drivers. We propose that in combining hydrologic and sediment connectivity into a single conceptual model, patterns emerge such that catchments will exist in a single characteristic behavior at a particular instance, which would shift with space and time, and with landscape disturbances. Using the conceptual model as a “thinking” tool, we extract case studies from a multidisciplinary literature review—from hydrology, geomorphology, biogeochemistry, and watershed modeling to remote-sensing technology—that correspond to each of the dominant hydrologic–sediment connectivity regimes. Sediment and water interactions in real-world examples through various observational and modeling techniques illustrate the advancements in the spatial and temporal scales of landscape connectivity observations and simulations. The conceptual model and case studies provide a foundation for advancing the understanding and predictive capability of watershed sediment processes at multiple spatiotemporal scales. Plain language summary: Soil erosion and movement across the landscape are closely linked to rain events and flow pathways. Landscape connectivity is a way to consider how soil erosion from different parts of the landscape is connected to the streams. We explore where soil erosion occurs and how eroded soil moves across the landscape through the interaction with rainfall and drainage. The comprehensive understanding of sediment connectivity and its dependence on rainfall characteristics and watershed hydrology may help to inform the effective distribution of conservation funds and management actions to address water pollution from excess sediment.

Frontiers in Water↗

USGS2013

Descriptors of natural thermal regimes in streams and their responsiveness to change in the Pacific Northwest of North America

1. Temperature is a major driver of ecological processes in stream ecosystems, yet the dynamics of thermal regimes remain poorly described. Most work has focused on relatively simple descriptors that fail to capture the full range of conditions that characterise thermal regimes of streams across seasons or throughout the year. 2. To more completely describe thermal regimes, we developed several descriptors of magnitude, variability, frequency, duration and timing of thermal events throughout a year. We evaluated how these descriptors change over time using long-term (1979–2009), continuous temperature data from five relatively undisturbed cold-water streams in western Oregon, U.S.A. In addition to trends for each descriptor, we evaluated similarities among them, as well as patterns of spatial coherence, and temporal synchrony. 3. Using different groups of descriptors, we were able to more fully capture distinct aspects of the full range of variability in thermal regimes across space and time. A subset of descriptors showed both higher coherence and synchrony and, thus, an appropriate level of responsiveness to examine evidence of regional climatic influences on thermal regimes. Most notably, daily minimum values during winter–spring were the most responsive descriptors to potential climatic influences. 4. Overall, thermal regimes in streams we studied showed high frequency and low variability of cold temperatures during the cold-water period in winter and spring, and high frequency and high variability of warm temperatures during the warm-water period in summer and autumn. The cold and warm periods differed in the distribution of events with a higher frequency and longer duration of warm events in summer than cold events in winter. The cold period exhibited lower variability in the duration of events, but showed more variability in timing. 5. In conclusion, our results highlight the importance of a year-round perspective in identifying the most responsive characteristics or descriptors of thermal regimes in streams. The descriptors we provide herein can be applied across hydro-ecological regions to evaluate spatial and temporal patterns in thermal regimes. Evaluation of coherence and synchrony of different components of thermal regimes can facilitate identification of impacts of regional climate variability or local human or natural influences.

Freshwater Biology↗

USGS2021

A novel automatic phenology learning (APL) method of training sample selection using multiple datasets for time-series land cover mapping

The long record of Landsat imagery, which is the cornerstone of Earth observation, provides an opportunity to monitor land use and land cover (LULC) change and understand the interactions between the climate and earth system through time. A few change detection algorithms such as Continuous Change Detection and Classification (CCDC) have been developed to utilize all available Landsat images for change detection and characterization at local or global scales. However, the reliable, rapid, and reproducible collection of training samples have become a challenge for time series land cover classification at a large scale. To meet the challenge, we proposed an automatic phenology learning (APL) method with the assumption that the temporal profiles of samples within the same land cover type are the same or similar at a local scale to generate evenly distributed training samples automatically. We designed the method to build land cover patterns for each category based on consensus samples derived from multiple existing scientific datasets including LANDFIRE's (LF) Existing Vegetation Type (EVT), USGS National Land Cover Database (NLCD), National Agricultural Statistics Service (NASS) Cropland Data Layer (CDL), and National Wetlands Inventory (NWI). Then we calculated the Time-Weighted Dynamic Time Warping (twDTW) distance between any undefined samples and land cover patterns in the same geographical region as prior knowledge. Finally, we selected the optimal land cover category for each undefined sample from the land cover products based on the designed criteria iteratively using the twDTW distance as an indicator. The method was applied in the footprint of 10 selected Landsat Analysis Ready Data (ARD) tiles in the eastern and western conterminous United States (CONUS) to produce annual land cover maps from 1985 to 2017. The accuracy assessment and visual comparison revealed that the APL method can generate reliable training samples without any manual interpretation, producing better land cover results especially for the grass/shrub and wetland land cover classes. Applying the APL method, the overall accuracy of the annual land cover maps was improved by 2% over the accuracy of Land Change Monitoring, Assessment, and Projection (LCMAP) Collection 1.0 Science Products in the research regions. Our results also indicate that the APL method provides an approach for best use of different land cover products and meets the requirement of intensive sampling for training data collection.

Remote Sensing of Environment↗

USGS2025

Disparate groundwater responses to wildfire

Post-wildfire investigations of groundwater response reveal a range of outcomes, varying from substantial increases to notable decreases in recharge and baseflow, with some studies indicating negligible or short-lived effects. This review assesses these varied responses within five critical categories: climate, vegetation, hydrogeology, fire characteristics, and the cryosphere, examining both short-term (within 2 years) and intermediate (2–10 years post-fire) effects. Despite considerable variability, some consistent patterns emerge. For instance, in hydroclimatic settings where water input and evaporative demand cycles are out of sync, post-wildfire groundwater responses tend to be positive (i.e., increased flux or storage), whereas under low fire severity conditions or in vegetation types that quickly recover, groundwater responses tend to be negative (i.e., decreased flux or storage). We synthesize relevant findings into a compendium of testable hypotheses aimed at explaining the spatiotemporal variability in observed post-wildfire groundwater responses. A recurring theme is the critical influence of the pre-wildfire groundwater regime on expected response and recovery. We identify opportunities for specific improvements in post-wildfire monitoring and modeling that would further advance capabilities to predict groundwater response. A key area for further research is understanding how wildfire effects on snow dynamics and other cryospheric processes translate to changes in groundwater.

WIREs Water↗

USGS2006

Forest reproduction along a climatic gradient in the Sierra Nevada, California

To elucidate broad-scale environmental controls of coniferous forest reproduction in the Sierra Nevada, California, we monitored reproduction for 5 years in 47 plots arrayed across a steep elevational (climatic) gradient. We found that both absolute seedling densities (stems < 1.37 m) and seedling densities relative to overstory parent tree basal area declined sharply with elevation. Rates of seedling turnover (the average of birth and death rates) also declined with elevation. In contrast, seed production was not predicted by elevation and was highly variable from year to year. During a mast year of seed production, the intensity of masting was uneven among plots. Seedling densities were elevated only during the single year immediately following the mast year, suggesting reproduction in our forests may be primarily limited by abiotic factors such as the availability of suitable sites and weather. Disturbance also clearly affected reproduction; plots that had recently burned had significantly higher seedling to parent tree ratios for Abies species, suggesting that even though established Abies concolor may be relatively susceptible to fire, the species can recover rapidly through prolific reproduction. Since reproductive failures may be our earliest signal of changing forest conditions, seedling dynamics could provide a sensitive, if variable, indicator of environmental changes.

California↗

USGS2018

El Niño/Southern Oscillation-driven rainfall pulse amplifies predation by owls on seabirds via apparent competition with mice

Most approaches for assessing species vulnerability to climate change have focused on direct impacts via abiotic changes rather than indirect impacts mediated by changes in species interactions. Changes in rainfall regimes may influence species interactions from the bottom-up by increasing primary productivity in arid environments, but subsequently lead to less predictable top-down effects. Our study demonstrates how the effects of an EL Niño/Southern Oscillation (ENSO)-driven rainfall pulse ricochets along a chain of interactions between marine and terrestrial food webs, leading to enhanced predation of a vulnerable marine predator on its island breeding grounds. On Santa Barbara Island, barn owls ( Tyto alba ) are the main predator of a nocturnal seabird, the Scripps's murrelet ( Synthliboramphus scrippsi ), as well as an endemic deer mouse. We followed the links between rainfall, normalized difference vegetation index and subsequent peaks in mouse and owl abundance. After the mouse population declined steeply, there was approximately 15-fold increase in the number of murrelets killed by owls. We also simulated these dynamics with a mathematical model and demonstrate that bottom-up resource pulses can lead to subsequent declines in alternative prey. Our study highlights the need for understanding how species interactions will change with shifting rainfall patterns through the effects of ENSO under global change.

California↗

USGS2024

Mitigating disparate elevation differences between adjacent topobathymetric data models using binary code

Integrating coastal topographic and bathymetric data for creating regional seamless topobathymetric digital elevation models of the land/water interface presents a complex challenge due to the spatial and temporal gaps in data acquisitions. The Coastal National Elevation Database (CoNED) Applications Project develops topographic (land elevation) and bathymetric (water depth) regional scale digital elevation models by integrating multiple sourced disparate topographic and bathymetric data models. These integrated regional models are broadly used in coastal and climate science applications, such as sediment transport, storm impact, and sea-level rise modeling. However, CoNED’s current integration method does not address the occurrence of measurable vertical discrepancies between adjacent near-shore topographic and bathymetric data sources, which often create artificial barriers and sinks along their intersections. To tackle this issue, the CoNED project has developed an additional step in its integration process that collectively assesses the input data to define how to transition between these disparate datasets. This new step defines two zones: a micro blending zone for near-shore transitions and a macro blending zone for the transition between high-resolution (3 m or less) to moderate-resolution (between 3 m and 10 m) bathymetric datasets. These zones and input data sources are reduced to a multidimensional array of zeros and ones. This array is compiled into a 16-bit integer representing a vertical assessment for each pixel. This assessed value provides the means for dynamic pixel-level blending between disparate datasets by leveraging the 16-bit binary notation. Sample site RMSE assessments demonstrate improved accuracy, with values decreasing from 0.203–0.241 using the previous method to 0.126–0.147 using the new method. This paper introduces CoNED’s unique approach of using binary code to improve the integration of coastal topobathymetric data.

Remote Sensing↗

USGS2012

Ecosystem services from converted land: the importance of tree cover in Amazonian pastures

Deforestation is responsible for a substantial fraction of global carbon emissions and changes in surface energy budgets that affect climate. Deforestation losses include wildlife and human habitat, and myriad forest products on which rural and urban societies depend for food, fiber, fuel, fresh water, medicine, and recreation. Ecosystem services gained in the transition from forests to pasture and croplands, however, are often ignored in assessments of the impact of land cover change. The role of converted lands in tropical areas in terms of carbon uptake and storage is largely unknown. Pastures represent the fastest-growing form of converted land use in the tropics, even in some areas of rapid urban expansion. Tree biomass stored in these areas spans a broad range, depending on tree cover. Trees in pasture increase carbon storage, provide shade for cattle, and increase productivity of forage material. As a result, increasing fractional tree cover can provide benefits land managers as well as important ecosystem services such as reducing conversion pressure on forests adjacent to pastures. This study presents an estimation of fractional tree cover in pasture in a dynamic region on the verge of large-scale land use change. An appropriate sampling interval is established for similar studies, one that balances the need for independent samples of sufficient number to characterize a pasture in terms of fractional tree cover. This information represents a useful policy tool for government organizations and NGOs interested in encouraging ecosystem services on converted lands. Using high spatial resolution remotely sensed imagery, fractional tree cover in pasture is quantified for the municipality of Rio Branco, Brazil. A semivariogram and devolving spatial resolution are employed to determine the coarsest sampling interval that may be used, minimizing effects of spatial autocorrelation. The coarsest sampling interval that minimizes spatial dependence was about 22 m. The area-weighted fractional tree cover for the study area was 1.85 %, corrected for a slight bias associated with the coarser sampling resolution. The pastures sampled for fractional tree cover were divided between ‘high’ and ‘low’ tree cover, which may be the result of intentional incorporation of arboreal species in pasture. Further research involving those ranchers that have a higher fractional tree cover may indicate ways to promote the practice on a broader scale in the region.

Urban Ecosystems↗

USGS2011

Water availability and use pilot: A multiscale assessment in the U.S. Great Lakes Basin

Beginning in 2005, water availability and use were assessed for the U.S. part of the Great Lakes Basin through the Great Lakes Basin Pilot of a U.S. Geological Survey (USGS) national assessment of water availability and use. The goals of a national assessment of water availability and use are to clarify our understanding of water-availability status and trends and improve our ability to forecast the balance between water supply and demand for future economic and environmental uses. This report outlines possible approaches for full-scale implementation of such an assessment. As such, the focus of this study was on collecting, compiling, and analyzing a wide variety of data to define the storage and dynamics of water resources and quantify the human demands on water in the Great Lakes region. The study focused on multiple spatial and temporal scales to highlight not only the abundant regional availability of water but also the potential for local shortages or conflicts over water. Regional studies provided a framework for understanding water resources in the basin. Subregional studies directed attention to varied aspects of the water-resources system that would have been difficult to assess for the whole region because of either data limitations or time limitations for the project. The study of local issues and concerns was motivated by regional discussions that led to recent legislative action between the Great Lakes States and regional cooperation with the Canadian Great Lakes Provinces. The multiscale nature of the study findings challenges water-resource managers and the public to think about regional water resources in an integrated way and to understand how future changes to the system-driven by human uses, climate variability, or land-use change-may be accommodated by informed water-resources management.

Great Lakes Basin↗

USGS2021

Spatiotemporal dynamics of insect pollinator communities in sagebrush steppe associated with weather and vegetation

The conservation of native insect pollinators is hampered by a lack of information about environmental factors influencing pollinator communities. We investigated how insect pollinator communities, composed of bees (Hymenoptera), butterflies and moths (Lepidoptera), and flies (Diptera), are influenced by spatial and temporal aspects of the environment in sagebrush steppe shrublands. We assessed hypotheses regarding spatial autocorrelation of communities, inter-annual variability in communities, influence of elevation on timing of emergence, and influence of weather on seasonal changes in relative abundance of different pollinator taxa. We captured 27,310 insects from 6 bee families, 27 butterfly and moth families, and 3 fly families. The occurrence of insect pollinators among sampling plots was not spatially autocorrelated, indicating that insect communities may be structured by habitat variation and microclimates over relatively fine spatial scales. Pollinator familial richness, diversity, abundance, and timing of emergence were most strongly positively associated with spatiotemporal variation in minimum daily temperatures at the ground surface during the active season. Emergence timing was positively correlated with growing degree days and percent humidity, regardless of elevation. All pollinator groups varied in abundance throughout their active season, peaking in early July (bees), late July (flies), or early August (butterflies and moths). Our findings suggest that changes in nighttime temperatures, which have been steadily increasing over the last several decades as a result of climate change, may have strong effects on sagebrush steppe pollinator communities. Also, non-bee pollinators may provide particularly important pollination in this vast ecosystem during the warmest time of the year.

Oregon↗

USGS2018

The relative importance of intrinsic and extrinsic drivers to population growth vary among local populations of Greater Sage-Grouse: An integrated population modeling approach

Consideration of ecological scale is fundamental to understanding and managing avian population growth and decline. Empirically driven models for population dynamics and demographic processes across multiple spatial scales can be powerful tools to help guide conservation actions. Integrated population models (IPMs) provide a framework for better parameter estimation by unifying multiple sources of data (e.g., count and demographic data). Hierarchical structure within such models that include random effects allow for varying degrees of data sharing across different spatiotemporal scales. We developed an IPM to investigate Greater Sage-Grouse ( Centrocercus urophasianus ) on the border of California and Nevada, known as the Bi-State Distinct Population Segment. Our analysis integrated 13 years of lek count data ( n > 2,000) and intensive telemetry (VHF and GPS; n > 350 individuals) data across 6 subpopulations. Specifically, we identified the most parsimonious models among varying random effects and density-dependent terms for each population vital rate (e.g., nest survival). Using a joint likelihood process, we integrated the lek count data with the demographic models to estimate apparent abundance and refine vital rate parameter estimates. To investigate effects of climatic conditions, we extended the model to fit a precipitation covariate for instantaneous rate of change ( r ). At a metapopulation extent (i.e. Bi-State), annual population rate of change λ ( e r ) did not favor an overall increasing or decreasing trend through the time series. However, annual changes in λ were driven by changes in precipitation (one-year lag effect). At subpopulation extents, we identified substantial variation in λ and demographic rates. One subpopulation clearly decoupled from the trend at the metapopulation extent and exhibited relatively high risk of extinction as a result of low egg fertility. These findings can inform localized, targeted management actions for specific areas, and status of the species for the larger Bi-State.

The Auk↗