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At least 793 records · Page 44Linked to original sources
USGS2019

Effects of flood inundation, invasion by Phalaris arundinacea, and nitrogen enrichment on extracellular enzyme activity in an Upper Mississippi River floodplain forest

The community structures and ecosystem functions of floodplains are primarily driven by variation in flood inundation. However, global changes, such as invasive species and nutrient enrichment, may alter the effects of flooding in these systems. We added nitrogen (N) to correspond with twice the annual atmospheric deposition rate of the south-west Wisconsin, USA region within mature floodplain forest plots and patches of an invasive grass (reed canarygrass, Phalaris arundinacea ) along a floodplain elevation gradient in an Upper Mississippi River floodplain forest. We measured soil physicochemical properties and the activity of six extracellular enzymes during 3 months that varied in flooding conditions. Multivariate analyses (distance-based redundancy analysis) revealed that floodplain elevation, month of sampling, and vegetation type were all significant predictors of variation in soil physicochemical properties, while elevation and month were significant predictors of multivariate extracellular enzyme activity (EEA). The best model for predicting EEA consisted of nitrogen availability, soil porosity, and water filled pore space. Although the categorical fertilization and invasion treatments were not significant predictors of EEA, our results suggest that their effects depend on the degree to which they modify N availability and soil moisture. In this system, spatial and temporal patterns in flooding appear to be the main driver of these properties, but N enrichment and invasion may have the potential to further modify them.

Wisconsin↗
USGS2003

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

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

Information and Technology Report↗
USGS2010

The use of scenario analysis to assess water ecosystem services in response to future land use change in the Willamette River Basin, Oregon

Human pressures on the natural resources of the United States have resulted in many unintended changes in our ecosystems, e.g., loss of biodiversity, habitat degradation, increases in the number of endangered species, and increases in contamination and water pollution. Environmental managers are concerned about broad-scale changes in land use and landscape pattern and their cumulative impact on hydrologic and ecological processes that affect stream conditions. The type of land use and land cover has direct consequences for most ecosystem services, including water quantity and water quality, erosion control, and biodiversity. As human pressure continues to increase, ecosystem services worldwide are projected to suffer continued loss and degradation, thus reducing the capacity of ecosystems to provide essential goods and services that contribute to human well-being (MEA 2005). The ability to assess, report, and forecast the life support functions of ecosystems is absolutely critical to our capacity to make informed decisions which will maintain the sustainable nature of our environmental services and secure these resources into the future. This study presents an integrated approach to identify areas with potential water quality problems as a result of land cover change projected by stakeholders within a moderately large river basin in the Pacific Northwest (USA). A process-based hydrologic watershed model was used to examine the contribution of land use/land cover to sediment yield, and nitrate and phosphorous loadings, and identify subwatersheds within the Willamette River basin that would be most affected in the year 2050 relative to three possible future scenarios which include inherent differences related to conservation, existing planning trends, and open development. Thus, the objective of this study was to evaluate the effects of alternative future scenarios that describe varying degrees of urban development and human use on hydrological response related to water quality. Results of this study suggest that the amount of forest along streams and agriculture consistently explained a high percentage of variation in nutrients. The AGWA-SWAT model was used to simulate change in sediment yield, nitrate and phosphorus transported with surface runoff for the three future scenarios. With regard to nitrate, the greatest increase was associated with subwatersheds with agricultural land use and urban areas. Although the model predicted some improvement in basin headwaters for all scenarios, nitrate loadings are expected to decrease under the conservation scenario. The largest decrease was observed in the Coast Range. With regard to phosphorous loadings, the lowest reduction was observed in subwatersheds draining predominantly forest areas. The greatest increase was observed under the open development scenario in subwatersheds with agricultural land use. Urbanization and agriculture are presumed to be the major environmental stressors affecting watershed condition of the Willamette River Basin.

Oregon↗
USGS2019

Activity patterns of cave-dwelling bat species during pre-hibernation swarming and post-hibernation emergence in the central Appalachians

In North America, bat research efforts largely have focused on summer maternity colonies and winter hibernacula, leaving the immediate pre- and post-hibernation ecology for many species unstudied. Understanding these patterns and processes is critical for addressing potential additive impacts to White-nose Syndrome (WNS)-affected bats, as autumn is a time of vital weight gain and fat resources are largely depleted in early spring in surviving individuals. Our study sought to examine autumn and spring bat activity patterns in the central Appalachian Mountains around three hibernacula to better understand spatio-temporal patterns during staging for hibernation and post-hibernation migration in the post-WNS environment. From early September through November 2015 and 2016, and from early March through April 2016 and 2017, we assessed the effects of distance to hibernacula and ambient conditions on nightly bat activity for Myotis spp. and big brown bats ( Eptesicus fuscus ) using zero-crossing frequency division bat detectors near cave entrances and 1 km, 2 km, and 3 km distant from caves. Following identification of echolocation calls, we used generalized linear mixed effects models to examine patterns of activity across the landscape over time and relative to weather. Overall bat activity was low at all sample sites during autumn and spring periods except at sites closest to hibernacula. Best-supported models describing bat activity varied, but date and ambient temperatures generally appeared to be major drivers of activity in both seasons. Total activity for all species had largely ceased by mid-November. Spring bat activity was variable across the sampling season, however, some activity was observed as early as mid-March, almost a month earlier than the historically accepted emergence time regionally. Current timing of restrictions on forest management activities that potentially remove day-roosts near hibernacula when bats are active on the landscape may be mismatched with actual spring post-hibernation emergence. Adjustments to the timing of these restrictions during the spring may help to avoid potentially additive negative impacts on WNS-impacted bat species.

Diversity↗
USGS2024

Effectiveness of canine-assisted surveillance and human searches for early detection of invasive spotted lanternfly

Prevention and early detection of invasive species are championed as the most cost-effective and efficient strategies for reducing or preventing negative impacts on ecosystems. Spotted lanternfly (SLF), Lycorma delicatula , is a recently introduced invasive insect whose range in the United States has been expanding rapidly since it was first discovered in Pennsylvania in 2014. Feeding by this planthopper can cause severe impacts on agricultural production, particularly grapes ( Vitis spp.). Human visual surveys are the most common search method employed for detection but can be ineffective due to the insect's cryptic egg masses and low density during early stages of infestation. Therefore, finding alternative early detection methods has become a priority for agencies tasked with addressing SLF management. This study experimentally tested whether trained detector dogs could improve the probability of detecting SLF in both agricultural and forest settings. We surveyed transects in 20 vineyards and their adjacent wooded areas in Pennsylvania and New Jersey, USA, and used a multiscale occupancy model to estimate detection probability achieved by human observers and detection dogs as a function of SLF infestation level, weather, and habitat covariates. We modeled transect-level occupancy of SLF as a function of infestation level, habitat type, topographic position index, and distance to forests. Occupancy probability of SLF was higher on vines within vineyards than in forests, and occupancy declined with increasing distance from forests, which is informative for future search efforts. Detection probability of SLF was lower at forested sites but was higher at high infestation sites. Detection dogs had a lower detection probability than humans in the vineyards, but the detection probability of dogs was >3× greater than that of humans in forested sites. Our study suggests that detection dogs are more effective than human visual searches as an early detection method for SLF in forested areas, and utilizing detector dogs could strengthen SLF early detection efforts. This study demonstrates the potential applicability of using canine-assisted search strategies combined with occupancy models to enhance the surveillance and prevention of other difficult-to-detect invasive species.

New Jersey, Pennsylvania↗
USGS2007

Mountain Lions of the Flagstaff Uplands: 2003-2006 Progress Report

Executive Summary Stakeholders in management of mountain lions in the Flagstaff Uplands of northern Arizona have expressed increasing concern about both potential impacts of humans on lions and potential risks posed by lions to humans. A series of human-mountain lion encounters during 2000-2001 on Mt. Elden, immediately adjacent to Flagstaff, and similar incidents during 2004 near Tucson brought increased attention to management of human safety in mountain lion range. These human-centered concerns, together with long-standing questions about how the human infrastructure centered on Flagstaff might be affecting lion movements led us to initiate a mountain lion study in 2003 which we plan to continue through 2009. Our study focuses on movements and other behaviors of mountain lions, with the goal of providing information that can be used to increase human safety, decrease human impacts, and, overall, provide insight into the ecology of lions in this region. To serve this goal, we have focused on collecting data that will be the basis of explanatory models that can provide spatially-explicit predictions of mountain lion activity, specify the effects of human facilities, such as highways and urban areas, and provide insight into when, where, and how often different kinds of lions kill different kinds of prey. During 2003-2006, we captured six female and five male mountain lions in the Flagstaff Uplands, 10 of which we fitted with collars that collected up to six high-precision GPS fixes per day, transmitted daily to our offices via Argos satellites. This timely delivery of data allowed us to visit kill sites and other foci of localized activity to collect detailed information on lion behavior. By June 2006 we had obtained 9357 GPS locations and visited 394 sites, at which we documented 218 kills, 165 of which were by five females and 53 by five males. These data were the basis for preliminary analyses presented in this report. All lions during all seasons exhibited a strong selection for rough terrain and forest or woodland cover. Females differed from males by selecting more strongly for intermediate, rather than extreme, levels of terrain roughness, by selecting more strongly for chaparral vegetation and related rocky areas during winter, and by not selecting as strongly for areas near water sources. Overall, lions collared during this study strongly avoided flat open areas in private ownership. Male but not female lions exhibited pronounced selection for National Park Service jurisdictions. Both males and females year-round avoided residential areas and a zone outward to about 1-3 km and, when within this zone, moved more slowly and with less change in direction compared to when farther away. Collared lions have so far rarely crossed paved highways of any description - orders of magnitude less often than expected by chance. We observed only 3 crossings of an interstate highway, all on I17 and none on I40. Elk comprised the majority (52%) of kills by lions in our study, followed by mule deer (46%), and small mammals (15%). Adults comprised most of the mule deer kills (68%) and mesocarnivores, primarily coyotes (n = 21), comprised 73% of smaller prey. Calf and short-yearling elk comprised the largest single category of kills (29%). In addition to kills, we documented seven instances of scavenging, involving four different lions. Females differed from males by killing more mule deer and virtually all of the mesocarnivores, and by killing fewer elk of all ages. Intervals between kills averaged between 144 hrs (young females) to 221 hours (adult females), whereas average time spent on a kill ranged from 19 hrs (adult males) to 40 hrs (young males). Carcass mass had a strong effect on likelihood that a lion would bury or relocate a kill, the percentage of edibles consumed, and overall time spent feeding. Time spent feeding and likelihoods of carcass burial and relocation all peaked at intermediate carcass masses, suggesting an optimal mass in the range of 50-150 kg, likely dictated as much by handling efficiencies and competition from other scavengers as by a lion's shear ability to kill prey. Adult male lions exhibited a life strategy distinctly different from all other sex-age classes that entailed moving more rapidly over larger areas, and spending less time on kills in which they invested less energy handling, but from which they consumed tissue at a higher sustained rate.

Open-File Report↗
USGS2013

Climate-associated population declines reverse recovery and threaten future of an iconic high-elevation plant

Although climate change is predicted to place mountain-top and other narrowly endemic species at severe risk of extinction, the ecological processes involved in such extinctions are still poorly resolved. In addition, much of this biodiversity loss will likely go unobserved, and therefore largely unappreciated. The Haleakalā silversword is restricted to a single volcano summit in Hawai‘i, but is a highly charismatic giant rosette plant that is viewed by 1–2 million visitors annually. We link detailed local climate data to a lengthy demographic record, and combine both with a population-wide assessment of recent plant mortality and recruitment, to show that after decades of strong recovery following successful management, this iconic species has entered a period of substantial climate-associated decline. Mortality has been highest at the lower end of the distributional range, where most silverswords occur, and the strong association of annual population growth rates with patterns of precipitation suggests an increasing frequency of lethal water stress. Local climate data confirm trends toward warmer and drier conditions on the mountain, and signify a bleak outlook for silverswords if these trends continue. The silversword example foreshadows trouble for diversity in other biological hotspots, and illustrates how even well-protected and relatively abundant species may succumb to climate-induced stresses.

Hawai'i↗
USGS2022

Similar environmental conditions are associated with Walleye and Yellow Perch recruitment success in Wisconsin lakes

Since the mid-2000s, recruitment of Walleye Sander vitreus in some northern Wisconsin lakes has declined, potentially because of climate-induced changes in lake environments. Yellow Perch Perca flavescens is also an ecologically and culturally important fish species in this region, but mechanisms driving Yellow Perch recruitment are unclear because of a lack of targeted sampling. Previous studies have suggested that recruitment of these two species may be regulated by similar factors, and observed declines in Walleye recruitment may be cause for concern about Yellow Perch recruitment. Our objectives were to determine if abiotic factors related to recruitment success were similar between Walleye and Yellow Perch populations in northern Wisconsin lakes and if the probability of successful Walleye recruitment was related to estimates of juvenile Yellow Perch abundance before Walleye recruitment declines were observed. We addressed these objectives using historical data from Wisconsin lakes. Random forest analysis incorporating lake-specific averages of predictor variables indicated that winter conditions (duration or severity), growing degree days, variation in spring temperatures, peak summer temperature, and Secchi depth were important predictors of recruitment success for both species. Logistic regression indicated that before Walleye recruitment declines were observed on some lakes (2000–2006), Walleye recruitment success was related to relative abundance of juvenile Yellow Perch in mini-fyke-net sampling. Our results indicate that landscape-level patterns in recruitment success for the two species are likely similar and additional research to understand Yellow Perch recruitment trends is warranted. Better information on Yellow Perch recruitment could contribute to a better understanding of Walleye recruitment trends as declines in Yellow Perch could influence prey availability and survival of age-0 Walleye. Furthermore, potential declines in Yellow Perch could lead to changes in the numbers and size of Yellow Perch caught by anglers, which may have implications for harvest management.

Wisconsin↗
USGS2012

Hierarchical distance-sampling models to estimate population size and habitat-specific abundance of an island endemic

Population size and habitat-specific abundance estimates are essential for conservation management. A major impediment to obtaining such estimates is that few statistical models are able to simultaneously account for both spatial variation in abundance and heterogeneity in detection probability, and still be amenable to large-scale applications. The hierarchical distance-sampling model of J. A. Royle, D. K. Dawson, and S. Bates provides a practical solution. Here, we extend this model to estimate habitat-specific abundance and rangewide population size of a bird species of management concern, the Island Scrub-Jay ( Aphelocoma insularis ), which occurs solely on Santa Cruz Island, California, USA. We surveyed 307 randomly selected, 300 m diameter, point locations throughout the 250-km 2 island during October 2008 and April 2009. Population size was estimated to be 2267 (95% CI 1613-3007) and 1705 (1212-2369) during the fall and spring respectively, considerably lower than a previously published but statistically problematic estimate of 12 500. This large discrepancy emphasizes the importance of proper survey design and analysis for obtaining reliable information for management decisions. Jays were most abundant in low-elevation chaparral habitat; the detection function depended primarily on the percent cover of chaparral and forest within count circles. Vegetation change on the island has been dramatic in recent decades, due to release from herbivory following the eradication of feral sheep ( Ovis aries ) from the majority of the island in the mid-1980s. We applied best-fit fall and spring models of habitat-specific jay abundance to a vegetation map from 1985, and estimated the population size of A. insularis was 1400-1500 at that time. The 20-30% increase in the jay population suggests that the species has benefited from the recovery of native vegetation since sheep removal. Nevertheless, this jay's tiny range and small population size make it vulnerable to natural disasters and to habitat alteration related to climate change. Our results demonstrate that hierarchical distance-sampling models hold promise for estimating population size and spatial density variation at large scales. Our statistical methods have been incorporated into the R package unmarked to facilitate their use by animal ecologists, and we provide annotated code in the Supplement.

California↗
USGS2007

Avifaunal responses to fire in southwestern montane forests along a burn severity gradient

The effects of burn severity on avian communities are poorly understood, yet this information is crucial to fire management programs. To quantify avian response patterns along a burn severity gradient, we sampled 49 random plots (2001-2002) at the 17 351-ha Cerro Grande Fire (2000) in New Mexico, USA. Additionally, pre-fire avian surveys (1986-1988, 1990) created a unique opportunity to quantify avifaunal changes in 13 pre-fire transects (resampled in 2002) and to compare two designs for analyzing the effects of unplanned disturbances: after-only analysis and before-after comparisons. Distance analysis was used to calculate densities. We analyzed after-only densities for 21 species using gradient analysis, which detected a broad range of responses to increasing burn severity: (I) large significant declines, (II) weak, but significant declines, (III) no significant density changes, (IV) peak densities in low- or moderate-severity patches, (V) weak, but significant increases, and (VI) large significant increases. Overall, 71% of the species included in the after-only gradient analysis exhibited either positive or neutral density responses to fire effects across all or portions of the severity gradient (responses III-VI). We used pre/post pairs analysis to quantify density changes for 15 species using before-after comparisons; spatiotemporal variation in densities was large and confounded fire effects for most species. Only four species demonstrated significant effects of burn severity, and their densities were all higher in burned compared to unburned forests. Pre- and post-fire community similarity was high except in high-severity areas. Species richness was similar pre- and post-fire across all burn severities. Thus, ecosystem restoration programs based on the assumption that recent severe fires in Southwestern ponderosa pine forests have overriding negative ecological effects are not supported by our study of post-fire avian communities. This study illustrates the importance of quantifying burn severity and controlling confounding sources of spatiotemporal variation in studies of fire effects. After-only gradient analysis can be an efficient tool for quantifying fire effects. This analysis can also augment historical data sets that have small samples sizes coupled with high non-process variation, which limits the power of before-after comparisons. ?? 2007 by the Ecological Society of America.

Ecological Applications↗
USGS2020

GoMAMN Strategic Bird Monitoring Guidelines: Landbirds

Landbirds in the Gulf of Mexico region include an ecologically diverse group of taxa that depend on a wide range of terrestrial habitats and the airspace above them. For the GoMAMN region of the Gulf of Mexico, the Landbird Working Group identified 19 species from 12 families as priorities for monitoring (Table 3.1). In addition, all species that stopover within the GoMAMN region during migration (i.e., passage migrants) are of concern, as are the habitats they use. The 19 priority species use a wide range of habitat types and include species that spend some (e.g., breeding, wintering, migration seasons) or all (e.g., residents) of their annual cycle in the GoMAMN region. The GoMAMN Landbird Working Group organized the priority landbirds into five groups based on a combination of habitat and season—forest breeding, forest wintering, grassland breeding, grassland wintering, and passage migrants—realizing that there would be overlap of habitats and seasons for some species. For example, Swainson's Warbler ( Limnothlypis swainsonii ) breeds in and migrates through forested habitat in the Gulf of Mexico region and Northern Bobwhite ( Colinus virginianus ) uses both prairie grasslands and evergreen forest (i.e., open pine savannas) (Table 3.1). For some species, such as Painted Bunting ( Passerina ciris ) and Common Ground-Dove ( Columbina passerina ), which often use scrub/shrub vegetation, the habitat-based designations above may be overly simplistic. Although it occurs along higher, drier fringes of palustrine and estuarine emergent marsh habitat, Sedge Wren ( Cistothorus platensis ) is included here as a landbird (rather than a marsh bird) because it is most commonly found during the winter along the Gulf coast in upland evergreen forest (i.e., wet pine savanna) habitat and grassland habitats. Selection of the five groups was predicated on the assumption that management efforts would be similar for species using these habitats in a given season, and that monitoring methods would be habitat and season specific.

Book chapter↗
USGS2022

Wildfire influences individual growth and breeding dispersal, but not survival and recruitment in a montane amphibian

Global wildfire regimes are changing rapidly, with widespread increases in the size, frequency, duration, and severity of wildfires. Whereas the effects of wildfire on ecological state variables such as occupancy, abundance, and species diversity are relatively well documented, changes in population vital rates (e.g., survival, recruitment) and individual responses (e.g., growth, movement) to wildfire are more limited because of the detailed information needed on the same individuals both pre- and post-fire. We capitalized on the 2018 Roosevelt wildfire, which occurred during our 6-year (2015–2020) capture–mark–recapture study of boreal toads ( Anaxyrus boreas boreas ; n = 1415) in the Bridger-Teton National Forest, USA, to evaluate the responses of population vital rates and individual metrics to wildfire. We employed robust design capture–recapture models to compare the growth, dispersal, survival, and recruitment of adult boreal toads pre- and post-fire at burned versus unburned sites. At burned locations, growth increased 2 years post-fire compared with the year directly following wildfire and was higher 2 years post-fire than any other interval during our study period. Boreal toads dispersed to alternative breeding patches more at burned sites than unburned sites and dispersal increased 2 years post-fire compared with the year directly following wildfire. Annual survival and recruitment neither differed between pre- and post-fire years nor among pre-fire years, the year following wildfire, and 2 years post-fire. We demonstrate that, in certain contexts, dispersal can play a major role in changes to state variables (e.g., abundance) after wildfire, as opposed to other vital rates such as survival and recruitment. Our study represents an important step toward understanding the biological processes that underlie observed patterns in state variables following wildfire, which ultimately will be critical for the effective management of species in landscapes experiencing shifts in fire activity.

Wyoming↗
USGS2019

UAV-derived estimates of forest structure to inform ponderosa pine forest restoration

Restoring forest ecosystems has become an increasingly high priority for land managers across the American West. Millions of hectares of forest are in need of drastic yet strategic reductions in density (e.g., basal area). Meeting the restoration and management goals requires quantifying metrics of vertical and horizontal forest structure, which has relied upon field‐based measurements, manned airborne or satellite remote sensing datasets. We used unmanned aerial vehicle (UAV ) image‐derived Structure‐from‐Motion (SfM) models and high‐resolution multispectral orthoimagery in this study to quantify vertical and horizontal forest structure at both the fine‐ (<4 ha) and mid‐scales (4–400 ha) across a forest density gradient. We then used these forest structure estimates to assess specific objectives of a forest restoration treatment. At the fine‐scale, we found that estimates of individual tree height and canopy diameter were most accurate in low‐density conditions, with accuracies degrading significantly in high‐density conditions. Mid‐scale estimates of canopy cover and forest density followed a similar pattern across the density gradient, demonstrating the effectiveness of UAV image‐derived estimates in low‐ to medium‐density conditions as well as the challenges associated with high‐density conditions. We found that post‐treatment conditions met a majority of the prescription objectives and demonstrate the UAV image application in quantifying changes from a mechanical thinning treatment. We provide a novel approach to forest restoration monitoring using UAV ‐derived data, one that considers varying density conditions and spatial scales. Future research should consider a more spatially extensive sampling design, including different restoration treatments, as well as experimenting with different combinations of equipment, flight parameters, and data processing workflows.

Western United States↗
USGS2019

Multi-resource analysis: A proof of concept study of natural resource tradeoffs in the Piceance Basin, Colorado, using the net resources assessment (NetRA) decision support tool

Executive Summary The U.S. Geological Survey (USGS) is developing a multi-resource analysis (MRA) line of products to inform land-use decision makers. Specifically, MRA products will integrate scientific information, include considerations for natural resource interrelations, and quantify the effects of resource management decisions in biophysical, economic, and societal terms. As part of the establishment of the MRA, the USGS, in collaboration with the University of New Mexico, has developed the Net Resources Assessment (NetRA) decision support tool. As a proof of concept analysis, the NetRA was applied to the Piceance basin in Colorado in a hypothetical example to illustrate how resource managers could use the NetRA to consider tradeoffs of natural resources among alternative development plans and land cover patterns within a geographic region. The NetRA is a policy-relevant approach to assess the availability of multiple natural resources. It is an analytical toolset that may be used to examine the spatiotemporal relations between development of energy and mineral resources and delivery of biological natural resources. The NetRA operates at multiple map scales and contains a set of integrated, compatible submodels with specific data requirements for natural resource stocks, engineering economics, biophysical, and ecological data for ecosystem services stocks, market prices, regulations, and nonmarket values. The NetRA includes an explicit process to consider the interdependence between development and conservation, which is a crucial consideration in land-management and land-use decisions. The NetRA is used to estimate an expected net resource value (NRV). The NRV is the expected, present value, economic benefit from the extraction of a resource (for example, natural gas) minus the total cost of production, which is the aggregation of the development, production, and social costs. Social costs include private costs plus any external costs. There can be external social benefits associated with natural gas production, such as increased demand for locally produced goods and increased employment in the local area through backward and forward linkages of natural gas production. The NRV is used to compare development outcomes (scenarios) from a range of exploration and development plans for cumulative energy production. The Piceance basin application of the NetRA uses the NRV to assess the tradeoff between continuous natural gas extraction and the effects to the local populations of Odocoileus hemionus (mule deer) and aquatic species and to consumptive water uses for an area the size and resolution of a USGS energy resource assessment unit. In the proof of concept simulation, the 2.9-square-mile-area of USGS oil and gas assessment unit 50200263 (Piceance basin continuous gas unit of the Mesaverde Total Petroleum System) was gridded into 588 cells. From this area, seven clusters with potential for development and three that cannot be developed were identified; the three clusters that cannot be developed were identified as wilderness study areas, areas of critical environmental concern, and national forests. On the basis of these criteria, there are 118 cells unsuitable for development in the oil and gas assessment unit: 84 are in national forests, 23 are areas of critical environmental concern, and 11 are wilderness study areas. The remaining cells in the oil and gas assessment unit can be developed on both private and public lands. Two scenarios were considered that are distinguished as plan 1 and plan 2. Plan 1 keeps the amount of land disturbance unchanged and limits the number of development locations to 140 grid cells for the production period, which constrains the amount of the energy resources available for development; the plan requires the usage of the Bureau of Land Management (BLM) unsuitability criteria. Plan 2 also limits the number of development locations to 140 grid cells for the production period but provides a constant volume of energy production by increasing the density of well pads within the cells. The effects of plan 2 to the NRV when there are five wells per pad and five pads per square mile happen mostly in the first 5 years of development, even though the effects on the population of mule deer continue in later years. This outcome is the result of the upfront development and investment costs and the initial effect to the ecosystem services.

Colorado↗
USGS2009

Addressing foundational elements of regional land-use change forecasting

Regional land-use models must address several foundational elements, including understanding geographic setting, establishing regional land-use histories, modeling process and representing drivers of change, representing local land-use patterns, managing issues of scale and complexity, and development of scenarios. Key difficulties include managing an array of biophysical and socioeconomic processes across multiple spatial and temporal scales, and acquiring and utilizing empirical data to support the analysis of those processes. The Southeastern and Pacific Northwest regions of the United States, two heavily forested regions with significant forest industries, are examined in the context of these foundational elements. Geographic setting fundamentally affects both the primary land cover (forest) in the two regions, and the structure and form of land use (forestry). Land-use histories of the regions can be used to parameterize land-use models, validate model performance, and explore land-use scenarios. Drivers of change in the two regions are many and varied, with issues of scale and complexity posing significant challenges. Careful scenario development can be used to simplify process-based land-use models, and can improve our ability to address specific research questions. The successful modeling of land-use change in these two areas requires integration of both top-down and bottom-up drivers of change, using scenario frameworks to both guide and simplify the modeling process. Modular approaches, with utilization and integration of existing process models, allow regional land-use modelers the opportunity to better represent primary drivers of land-use change. However, availability of data to represent driving forces remains a primary obstacle.

Landscape Ecology↗
USGS2003

A Benthic Community Index for streams in the Northern Lakes and Forests Ecoregion

Encompassing the northern glaciated section of the Midwest United States, the Northern Lakes and Forests Ecoregion is characterized by mixed conifer and deciduous forests and wetlands. Sites were randomly selected in the ecoregion using the Environmental Protection Agency's Environmental Monitoring and Assessment Program designed to develop an index of biotic integrity for wadeable streams. Macroinvertebrates were sampled during the fall of 1998 and 1999 using a multi-habitat, composite-sample method. Two hundred forty-six invertebrate taxa in 97 families were collected from 94 sites. Ten of 42 candidate metrics satisfied metric selection criteria, including six structural metrics (number of Ephemeroptera taxa, number of Diptera taxa, richness, Shannon-Wiener diversity, percent Trichoptera abundance, and percent Crustacea and Mollusca abundance), two functional metrics (number of Filterer taxa and number of Scraper taxa), and two conditional metrics (number of Ephemeroptera, Trichoptera, and Plecoptera taxa and Hilsenhoff Biotic Index). These metrics were used to develop a Benthic Community Index to assess the biological integrity of wadeable streams in the ecoregion. Index values ranged from 10 to 50, and scores from impaired sites were significantly different than non-impaired sites (P<0.001). Index values were divided into three narrative interpretations of biological integrity (poor, fair, and good). After further testing, the index may provide a useful biological assessment tool for resource managers in the ecoregion.

Ecological Indicators↗
USGS2023

A big data–model integration approach for predicting epizootics and population recovery in a keystone species

Infectious diseases pose a significant threat to global health and biodiversity. Yet, predicting the spatiotemporal dynamics of wildlife epizootics remains challenging. Disease outbreaks result from complex nonlinear interactions among a large collection of variables that rarely adhere to the assumptions of parametric regression modeling. We adopted a nonparametric machine learning approach to model wildlife epizootics and population recovery, using the disease system of colonial black-tailed prairie dogs (BTPD, Cynomys ludovicianus ) and sylvatic plague as an example. We synthesized colony data between 2001 and 2020 from eight USDA Forest Service National Grasslands across the range of BTPDs in central North America. We then modeled extinctions due to plague and colony recovery of BTPDs in relation to complex interactions among climate, topoedaphic variables, colony characteristics, and disease history. Extinctions due to plague occurred more frequently when BTPD colonies were spatially clustered, in closer proximity to colonies decimated by plague during the previous year, following cooler than average temperatures the previous summer, and when wetter winter/springs were preceded by drier summers/falls. Rigorous cross-validations and spatial predictions indicated that our final models predicted plague outbreaks and colony recovery in BTPD with high accuracy (e.g., AUC generally >0.80). Thus, these spatially explicit models can reliably predict the spatial and temporal dynamics of wildlife epizootics and subsequent population recovery in a highly complex host–pathogen system. Our models can be used to support strategic management planning (e.g., plague mitigation) to optimize benefits of this keystone species to associated wildlife communities and ecosystem functioning. This optimization can reduce conflicts among different landowners and resource managers, as well as economic losses to the ranching industry. More broadly, our big data–model integration approach provides a general framework for spatially explicit forecasting of disease-induced population fluctuations for use in natural resource management decision-making.

Arizona, Colorado, Kansas, Montana, Nebraska, New ↗
USGS2018

Promoting synergy in the innovative use of environmental data—Workshop summary

From December 2 to 4, 2015, NatureServe and the U.S. Geological Survey organized and hosted a biodiversity and ecological informatics workshop at the U.S. Department of the Interior in Washington, D.C. The workshop objective was to identify user-driven future directions and areas of collaboration in advanced applications of environmental data applied to forecasting and decision making for the sustainability of biodiversity and ecosystem services. Substantial effort to recruit attendees from diverse Federal, State, and private sector organizations successfully attracted participants from 20 Federal agencies and 48 different institutions in the academic, nonprofit, State government, and commercial sectors; the total number of attendees ranged from 100 to 144 during the 3-day workshop. The first one-half of the workshop was divided into 7 plenary sessions and 3 sets of lightning talk sessions organized by sector, providing 48 oral and visual plenary presentations that shared diverse perspectives on biodiversity and ecological informatics, including original biospatial analyses from 6 graduate student map contest winners. The second one-half of the workshop focused on 10 breakout sessions with participant-driven themes from the environmental data sphere and concluded with an address by the Director of the U.S. Fish and Wildlife Service. The workshop was structured to encourage interactivity. About 80–90 percent of attendees provided direct feedback using clicker devices for specific questions related to biodiversity and ecological data uses and needs, and 10 breakout session leaders shared the highlights of their group discussions during the final workshop plenary sessions. Participants were encouraged to use the Twitter hashtag #ShareUrData. Over lunch on day 2 there were 20 simultaneous presentations of tools and apps during a special “Tools Café” session. The 10 participant-defined breakout session topics are listed below: Ecosystem services and ecological indicators Inventory and monitoring Biogeographic map of the Nation Pollinators Invasive species Remote sensing Drivers of agricultural change Citizen science Climate Hydrology and watersheds Numerous common themes that emerged from the workshop include the following: The vital importance of completing foundational environmental datasets that are nationally consistent and are essential to multiple sectors, such as the Soil Survey Geographic database high-resolution soils data, a minimum 5-meter resolution digital elevation model, national hydrographic data, high-resolution land cover data, time series high-resolution spatial climate data from historical to future time steps, and a national wetland inventory. Improved, nationally consistent environmental datasets (integrated with targeted observations) will dramatically advance forecasting capacity and support early warning systems (that is, drought, forest disease); however, multiagency coordination should focus on decision support tools that convey appropriate actions and responses to adapt to, and mitigate, potential negative consequences. Digitizing and providing access to the vast stores of underused historical data that can be leveraged for this purpose is of national importance. Modern computational techniques and the ever-increasing flow of environmental data from ground and remote observations can support improved understanding of environmental change. Success of understanding patterns of change for decision making requires establishing baselines from which change can be measured. The value of digitized historical data is greater than ever before. There is a need to recognize the multifaceted potential of citizen science to engage the public in resource stewardship, to create the next generation of science, technology, engineering, math, and environmental leaders, and to have sufficient field personnel to monitor environmental trends, including early detection of alien invasive species, phenological shifts, shifting distribution and abundance of indicator species, and species inventories. The Federal government has an essential role in creating the infrastructure to dramatically improve mobilization of citizen science (and other) data by fostering the following: creation of data standards, creation of nationally consistent framework datasets, vertical integration of observation data, visualization and dissemination of aggregated datasets, and calculation and communication of derived trends. Current and near future trends in the availability of remotely sensed data (rapid expansion of satellite fleets and drones) is revolutionizing access to near-real-time ecological data. Targeted integration with ground-based observations and instrumentation has an extremely valuable role in validating remotely sensed data, filling data gaps, improving data quality, and fully realizing the potential of the near-real-time monitoring of environmental indicator trends. Integrated management of environmental data at the landscape scale is required even as specific actions on the ground are largely local in nature. The workshop highlighted numerous success stories; however, almost every breakout group pointed out the still-too-fragmented nature of the current data landscape. Management and delivery of the necessary data, tools, and analyses to sustain our Nation’s environmental capital must be a collaborative effort between Federal, State, and local governments, academia, nonprofits, and the commercial sector, even though the responsibilities of each sector are different.

Open-File Report↗