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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↗

USGS1990

Multiple scales of patchiness and patch structure: a hierarchical framework for the study of heterogeneity

We develop a hierarchical model of heterogeneity that provides a framework for classifying patch structure across a range of scales. Patches at lower levels in the hierarchy are more simplistic and correspond to the traditional view of patches. At levels approaching the upper bounds of the hierarchy the internal structure becomes more heterogeneous and boundaries more ambiguous. At each level in the hierarchy, patch structure will be influenced by both contrast among patches as well as the degree of aggregation of patches at lower levels in the hierarchy. We apply this model to foraging theory, but it has wider applications as in the study of habitat selection, population dynamics, and habitat fragmentation. It may also be useful in expanding the realm of landscape ecology beyond the current focus on anthropocentric scales.

Oikos↗

USGS1997

Analysis of habitat selection studies with multiple patches within cover types

Current statistical methods are inadequate for evaluation of the relation between spatial pattern of the landscape and observed patterns of habitat use by individuals or populations. For example, traditional habitat selection analysis methods do not use information about the size and distribution of the several patches of each cover type that may exist within the study area. Statistical tests are presented for hypotheses about disproportional use of cover types and patches within cover types. These tests require that use of individual patches is recorded, as well as the size of individual patches. Different designs are considered in which there are (1) single or multiple samples of use, and (2) equal or unequal habitat availability. Formulas for calculating Type II statistical errors of the tests are presented and Monte Carlo simulation is used to assess the accuracy of the formulas and to check the Type I error rates of the proposed test statistics. With adequate sample sizes, Type II error formulas can be a useful tool for planning of habitat selection studies. An example analysis is presented of a hypothetical study of habitat selection by ring-necked pheasants ( Phasianus colchicus ) in a Midwestern landscape. The proposed tests also represent a contribution toward bringing together concepts of landscape ecology and wildlife habitat selection.

Journal of Wildlife Management↗

USGS2013

An evaluation of the individual components and accuracies associated with the determination of impervious area

The percentage of impervious surface area in a watershed has been widely recognized as a key indicator of terrestrial and aquatic ecosystem condition. Although the use of the impervious indicator is widespread, there is currently no consistent or mutually accepted method of computing impervious area and the approach of various commonly used techniques varies widely. Further, we do not have reliable information on the components of impervious surfaces, which would be critical in any future planning attempts to remediate problems associated with impervious surface coverage. In cooperation with the USGS Geographic Analysis and Monitoring Program (GAM) and The National Map, and the EPA Landscape Ecology Program, this collaborative research project utilized very high resolution imagery and GIS techniques to map and quantify the individual components of total impervious area in six urban/suburban watersheds in different parts of the United States. These data were served as ground reference, or "truth," for the evaluation for four techniques used to compute impervious area. The results show some important aspects about the component make-up of impervious cover and the variability of methods commonly used to compile this critical emerging indicator of ecosystem condition.

GIScience and Remote Sensing↗

USGS2010

Attributes for NHDPlus Catchments (Version 1.1) for the Conterminous United States: Level 3 Ecoregions

This data set represents the estimated area of level 3 ecological landscape regions (ecoregions), as defined by Omernik (1987), compiled for every catchment of NHDPlus for the conterminous United States. The source data set is Level III Ecoregions of the Continental United States (U.S. Environmental Protection Agency, 2003). The NHDPlus Version 1.1 is an integrated suite of application-ready geospatial datasets that incorporates many of the best features of the National Hydrography Dataset (NHD) and the National Elevation Dataset (NED). The NHDPlus includes a stream network (based on the 1:100,00-scale NHD), improved networking, naming, and value-added attributes (VAAs). NHDPlus also includes elevation-derived catchments (drainage areas) produced using a drainage enforcement technique first widely used in New England, and thus referred to as "the New England Method." This technique involves "burning in" the 1:100,000-scale NHD and when available building "walls" using the National Watershed Boundary Dataset (WBD). The resulting modified digital elevation model (HydroDEM) is used to produce hydrologic derivatives that agree with the NHD and WBD. Over the past two years, an interdisciplinary team from the U.S. Geological Survey (USGS), and the U.S. Environmental Protection Agency (USEPA), and contractors, found that this method produces the best quality NHD catchments using an automated process (USEPA, 2007). The NHDPlus dataset is organized by 18 Production Units that cover the conterminous United States. The NHDPlus version 1.1 data are grouped by the U.S. Geologic Survey's Major River Basins (MRBs, Crawford and others, 2006). MRB1, covering the New England and Mid-Atlantic River basins, contains NHDPlus Production Units 1 and 2. MRB2, covering the South Atlantic-Gulf and Tennessee River basins, contains NHDPlus Production Units 3 and 6. MRB3, covering the Great Lakes, Ohio, Upper Mississippi, and Souris-Red-Rainy River basins, contains NHDPlus Production Units 4, 5, 7 and 9. MRB4, covering the Missouri River basins, contains NHDPlus Production Units 10-lower and 10-upper. MRB5, covering the Lower Mississippi, Arkansas-White-Red, and Texas-Gulf River basins, contains NHDPlus Production Units 8, 11 and 12. MRB6, covering the Rio Grande, Colorado and Great Basin River basins, contains NHDPlus Production Units 13, 14, 15 and 16. MRB7, covering the Pacific Northwest River basins, contains NHDPlus Production Unit 17. MRB8, covering California River basins, contains NHDPlus Production Unit 18.

Data Series↗

USGS2010

Attributes for MRB_E2RF1 Catchments by Major River Basins in the Conterminous United States: Level 3 Ecoregions

This tabular data set represents the estimated area of level 3 ecological landscape regions (ecoregions), as defined by Omernik (1987), compiled for every MRB_E2RF1 catchment of the Major River Basins (MRBs, Crawford and others, 2006). The source data set is Level III Ecoregions of the Continental United States (U.S. Environmental Protection Agency, 2003). The MRB_E2RF1 catchments are based on a modified version of the U.S. Environmental Protection Agency's (USEPA) ERF1_2 and include enhancements to support national and regional-scale surface-water quality modeling (Nolan and others, 2002; Brakebill and others, 2011). Data were compiled for every MRB_E2RF1 catchment for the conterminous United States covering New England and Mid-Atlantic (MRB1), South Atlantic-Gulf and Tennessee (MRB2), the Great Lakes, Ohio, Upper Mississippi, and Souris-Red-Rainy (MRB3), the Missouri (MRB4), the Lower Mississippi, Arkansas-White-Red, and Texas-Gulf (MRB5), the Rio Grande, Colorado, and the Great basin (MRB6), the Pacific Northwest (MRB7) river basins, and California (MRB8).

Data Series↗

USGS2002

Land use change and effects on water quality and ecosystem health in the Lake Tahoe basin, Nevada and California: year-1 progress

As part of the requirements for the Geographic Research and Applications Prospectus grants, this Open-File Report is the second of two that resulted from the first year of the project. The first Open-File Report (OFR 01-418) introduced the project, reviewed the existing body of literature, and outlined the research approach. This document will present an update of the research approach and offer some preliminary results from multiple efforts, specifically, the production of historical digital orthophoto quadrangles, the development of the land use/land cover (LULC) classification system, the development of a temporal transportation layer, the classification of anthropogenic cover types from the IKONOS imagery, a preliminary evaluation of landscape ecology metrics (quantification of spatial and temporal patterns of ecosystem structure and function with appropriate indices) and their utility in comparing two LULC systems, and a new initiative in community-based science and facilitation.

Open-File Report↗

USGS2013

Thermokarst and thaw-related landscape dynamics -- an annotated bibliography with an emphasis on potential effects on habitat and wildlife

Permafrost has warmed throughout much of the Northern Hemisphere since the 1980s, with colder permafrost sites warming more rapidly (Romanovsky and others, 2010; Smith and others, 2010). Warming of the near-surface permafrost may lead to widespread terrain instability in ice-rich permafrost in the Arctic and the Subarctic, and may result in thermokarst development and other thaw-related landscape features (Jorgenson and others, 2006; Gooseff and others, 2009). Thermokarst and other thaw-related landscape features result from varying modes and scales of permafrost thaw, subsidence, and removal of material. An increase in active-layer depth, water accumulation on the soil surface, permafrost degradation and associated retreat of the permafrost table, and changes to lake shores and coastal bluffs act and interact to create thermokarst and other thaw-related landscape features (Shur and Osterkamp, 2007). There is increasing interest in the spatial and temporal dynamics of thermokarst and other thaw-related features from diverse disciplines including landscape ecology, hydrology, engineering, and biogeochemistry. Therefore, there is a need to synthesize and disseminate knowledge on the current state of near-surface permafrost terrain. The term "thermokarst" originated in the Russian literature, and its scientific use has varied substantially over time (Shur and Osterkamp, 2007). The modern definition of thermokarst refers to the process by which characteristic landforms result from the thawing of ice-rich permafrost or the melting of massive ice (van Everdingen, 1998), or, more specifically, the thawing of ice-rich permafrost and (or) melting of massive ice that result in consolidation and deformation of the soil surface and formation of specific forms of relief (Shur, 1988). Jorgenson (2013) identifies 23 distinct thermokarst and other thaw-related features in the Arctic, Subarctic, and Antarctic based primarily on differences in terrain condition, ground-ice volume, and heat and mass transfer processes. Typical Arctic thermokarst landforms include thermokarst lakes, collapsed pingos, sinkholes, and pits. Thermokarst is differentiated from thermal erosion, which refers to the erosion of the land surface by thermal and mechanical processes (Mackay, 1970; van Everdingen, 1998). Typical thermal erosional features include thermo-erosional gullies. Thermal abrasion is further differentiated from thermokarst and thermal erosion by association with the reworking of ocean, river, and lake bluffs (Are, 1988). Typical thermo-abrasion features include erosional niches at the base of bluffs. Thermal denudation is another distinct term that refers to the effect of incoming solar energy on the thaw of frozen slopes and permafrost bodies that subsequently become transported downhill by gravity (Shur and Osterkamp, 2007). Active layer detachment slides and thaw slumps are typical thermal denudation features. Shur and Osterkamp (2007) noted that these various transport processes may occur together with thermokarst or in instances that would not be considered thermokarst. This compilation of references regarding thermokarst and other thaw-related features is focused on the Arctic and the Subarctic. References were drawn from North America as well as Siberia. English-language literature mostly was targeted, with 167 references annotated in version 1.0; however, an additional 28 Russian-language references were taken from Shur and Osterkamp (2007) and are provided at the end of this document. This compilation may be missing key references and inevitably will become outdated soon after publication. We hope that this document, version 1.0, will serve as the foundation for a comprehensive compilation of thermokarst and permafrost-terrain stability references, and that it will be updated continually over the coming years.

Open-File Report↗

USGS2011

Quantifying seascape structure: Extending terrestrial spatial pattern metrics to the marine realm

Spatial pattern metrics have routinely been applied to characterize and quantify structural features of terrestrial landscapes and have demonstrated great utility in landscape ecology and conservation planning. The important role of spatial structure in ecology and management is now commonly recognized, and recent advances in marine remote sensing technology have facilitated the application of spatial pattern metrics to the marine environment. However, it is not yet clear whether concepts, metrics, and statistical techniques developed for terrestrial ecosystems are relevant for marine species and seascapes. To address this gap in our knowledge, we reviewed, synthesized, and evaluated the utility and application of spatial pattern metrics in the marine science literature over the past 30 yr (1980 to 2010). In total, 23 studies characterized seascape structure, of which 17 quantified spatial patterns using a 2-dimensional patch-mosaic model and 5 used a continuously varying 3-dimensional surface model. Most seascape studies followed terrestrial-based studies in their search for ecological patterns and applied or modified existing metrics. Only 1 truly unique metric was found (hydrodynamic aperture applied to Pacific atolls). While there are still relatively few studies using spatial pattern metrics in the marine environment, they have suffered from similar misuse as reported for terrestrial studies, such as the lack of a priori considerations or the problem of collinearity between metrics. Spatial pattern metrics offer great potential for ecological research and environmental management in marine systems, and future studies should focus on (1) the dynamic boundary between the land and sea; (2) quantifying 3-dimensional spatial patterns; and (3) assessing and monitoring seascape change.

Marine Ecology Progress Series↗

USGS2003

Surveillance strategies for detecting Chronic Wasting Disease in free-ranging deer and elk: Results of a CWD surveillance workshop

Executive Summary Chronic Wasting Disease (CWD), a fatal brain disease of North American deer and elk, has recently emerged as an important wildlife management issue. Interest and concern over the spread of this disease and its potential impact on free-ranging cervid populations has increased with discovery of the disease in numerous states and provinces. Current studies suggest that CWD may adversely affect of these highly visible, socially desirable, and economically valuable species. Despite the lack of evidence that CWD affects humans or livestock, a significant concern has been the perceived risk to humans and livestock. Uncertainty about whether CWD poses a health risk to hunters and their families who consume venison has resulted in testing of free-ranging cervids for CWD. In response to many of these concerns, wildlife management agencies across the nation have undertaken surveillance programs to detect CWD in their cervid populations. The nation-wide costs for an extensive CWD surveillance program have been estimated at several million dollars. This document provides guidance on the development and conduct of scientifically sound surveillance programs to detect CWD in free-ranging deer and elk populations. These guidelines will not apply equally to all jurisdictions. In many cases local circumstances, resources, area(s) of concern, disease risk, animal and landscape ecology, political, social, and many other factors will influence the objectives, design, and conduct of CWD surveillance programs. Part I of this report discusses the importance of management goals, strategies, and disease risks in developing a surveillance program. Part II describes surveillance methods, steps in designing a sampling strategy to detect CWD, alternative collection methods, and statistical considerations. Part III describes costs (personnel, time, and money) associated with implementation of these plans that will influence program design. Part IV outlines research that is needed to further development of CWD surveillance methods. Unfortunately in dealing with CWD, many important biological facts are still unknown and further research will be required to answer these questions. In most situations surveillance strategies suggested may require several years to complete, will require careful consideration of management objectives, and extensive operational planning in order to be meaningful and to be scientifically based.

Book↗

USGS2013

WICCI Wildlife Working Group Report

Wisconsin is world-renowned for its diversity of ecological landscapes and wildlife populations. The northern forests, southern prairies, and interior and coastal wetlands of the state are home to more than 500 terrestrial animal species. These animals supply the Wisconsin public with aesthetic, cultural, and economic benefits; our identity and economy are intertwined with these natural resources. Climate change is altering the behavior, distribution, development, reproduction, and survival of these animal populations. In turn, these changes will alter the aesthetic, cultural, and economic benefits we receive from them. The focus of the Wildlife Working Group is to document past and current impacts, anticipate changes in wildlife distribution and abundance, and develop adaptation strategies to maintain the vitality and diversity of Wisconsin's wildlife populations.

Report↗

USGS2025

Mapping predicted ecological states at landscape scales using remote sensing data and machine learning

Dryland ecosystems, covering 45% of the Earth's land and supporting over one-third of the global population, face significant threats from land degradation and ecological state change. Managing these ecosystems is complex, and science-based frameworks like Ecological Site Descriptions and state-and-transition models are essential tools for guiding decisions to support ecological health while maintaining stakeholder values such as grazing, wildlife, and recreation. However, alignment of these frameworks with smaller scale soil survey maps limits their applicability to broader ecological processes. Here, we extend these frameworks to larger landscapes with a machine learning approach that integrates large-scale, high-resolution vegetation data with identified ecological states from a data-driven state-and-transition model developed for a landscape-scale Ecological Site Group. A “global” model, which used combined inputs from multiple remotely sensed datasets, outperformed individual dataset models based on evaluation with independent data. Ecological state maps generated through this approach broaden the utility of state-and-transition models across Ecological Site Groups, providing a more spatially robust tool for land management at watershed and larger landscape scales. These methods, and the associated ecological state maps, can help meet critical needs for improved land condition assessments that support development of resource management plans and help identify priority areas for restoration and conservation.

Arizona, Colorado, New Mexico, Utah, Wyoming↗

USGS2014

Biological soil crusts (biocrusts) as a model system in community, landscape and ecosystem ecology

Model systems have had a profound influence on the development of ecological theory and general principles. Compared to alternatives, the most effective models share some combination of the following characteristics: simpler, smaller, faster, general, idiosyncratic or manipulable. We argue that biological soil crusts (biocrusts) have unique combinations of these features that should be more widely exploited in community, landscape and ecosystem ecology. In community ecology, biocrusts are elucidating the importance of biodiversity and spatial pattern for maintaining ecosystem multifunctionality due to their manipulability in experiments. Due to idiosyncrasies in their modes of facilitation and competition, biocrusts have led to new models on the interplay between environmental stress and biotic interactions and on the maintenance of biodiversity by competitive processes. Biocrusts are perhaps one of the best examples of micro-landscapes—real landscapes that are small in size. Although they exhibit varying patch heterogeneity, aggregation, connectivity and fragmentation, like macro-landscapes, they are also compatible with well-replicated experiments (unlike macro-landscapes). In ecosystem ecology, a number of studies are imposing small-scale, low cost manipulations of global change or state factors in biocrust micro-landscapes. The versatility of biocrusts to inform such disparate lines of inquiry suggests that they are an especially useful model system that can enable researchers to see ecological principles more clearly and quickly.

Biodiversity and Conservation↗

USGS2002

The consequences of landscape change on ecological resources: An assessment of the United States mid-Atlantic region, 1973-1993

Spatially explicit identification of changes in ecological conditions over large areas is key to targeting and prioritizing areas for environmental protection and restoration by managers at watershed, basin, and regional scales. A critical limitation to this point has been the development of methods to conduct such broad-scale assessments. Field-based methods have proven to be too costly and too inconsistent in their application to make estimates of ecological conditions over large areas. New spatial data derived from satellite imagery and other sources, the development of statistical models relating landscape composition and pattern to ecological endpoints, and geographic information systems (GIS) make it possible to evaluate ecological conditions at multiple scales over broad geographic regions. In this study, we demonstrate the application of spatially distributed models for bird habitat quality and nitrogen yield to streams to assess the consequences of landcover change across the mid-Atlantic region between the 1970s and 1990s. Moreover, we present a way to evaluate spatial concordance between models related to different environmental endpoints. Results of this study should help environmental managers in the mid-Atlantic region target those areas in need of conservation and protection.

Ecosystem Health↗

USGS2006

Ecological and sampling constraints on defining landscape fire severity

Ecological definition and detection of fire severity are influenced by factors of spatial resolution and timing. Resolution determines the aggregation of effects within a sampling unit or pixel (alpha variation), hence limiting the discernible ecological responses, and controlling the spatial patchiness of responses distributed throughout a burn (beta variation). As resolution decreases, alpha variation increases, extracting beta variation and complexity from the spatial model of the whole burn. Seasonal timing impacts the quality of radiometric data in terms of transmittance, sun angle, and potential contrast between responses within burns. Detection sensitivity candegrade toward the end of many fire seasons when low sun angles, vegetation senescence, incomplete burning, hazy conditions, or snow are common. Thus, a need exists to supersede many rapid response applications when remote sensing conditions improve. Lag timing, or timesince fire, notably shapes the ecological character of severity through first-order effects that only emerge with time after fire, including delayed survivorship and mortality. Survivorship diminishes the detected magnitude of severity, as burned vegetation remains viable and resprouts, though at first it may appear completely charred or consumed above ground. Conversely, delayed mortality increases the severity estimate when apparently healthy vegetation is in fact damaged by heat to the extent that it dies over time. Both responses dependon fire behavior and various species-specific adaptations to fire that are unique to the pre-firecomposition of each burned area. Both responses can lead initially to either over- or underestimating severity. Based on such implications, three sampling intervals for short-term burn severity are identified; rapid, initial, and extended assessment, sampled within about two weeks, two months, and depending on the ecotype, from three months to one year after fire, respectively. Spatial and temporal conditions of sampling strategies constrain data quality and ecological information obtained about fire severity. Though commonly overlooked, such considerations determine the objectives and hypotheses that are appropriate for each application, and are especially important when building comparative studies or long-term reference databases on fire severity.

Fire Ecology↗

USGS2020

Near-term spatial hydrologic forecasting in Everglades, USA for landscape planning and ecological forecasting

Operational ecological forecasting is an emerging field that leverages ecological models in a new, cross-disciplinary way – using a real-time or nearly real-time climate forecast to project near-term ecosystem states. These applications give decision-makers lead time to anticipate and manage state changes that degrade ecosystem functions or directly impact humans. The Everglades Forecasting model (EverForecast) is an operational forecast model designed specifically for conservation management purposes including water management. It provides up to six-month forecasts of daily projected, spatially continuous stage values across the Everglades. We validated EverForecast quarterly to measured historical values at 207 gages (1 Jan 2000 – 31 Dec 2019). EverForecast hindcasted water stage accurately captured measured stage variation, with a low percentage of measured stage exceeding hindcasted values. Over the whole spatial extent, the mean RMSE is 20.98 cm, the mean MAE is 14.42 cm, and the mean MBE is 0.91 cm.

Florida↗

USGS2014

Modelling non-Euclidean movement and landscape connectivity in highly structured ecological networks

Movement is influenced by landscape structure, configuration and geometry, but measuring distance as perceived by animals poses technical and logistical challenges. Instead, movement is typically measured using Euclidean distance, irrespective of location or landscape structure, or is based on arbitrary cost surfaces. A recently proposed extension of spatial capture-recapture (SCR) models resolves this issue using spatial encounter histories of individuals to calculate least-cost paths (ecological distance: Ecology , 94 , 2013, 287) thereby relaxing the Euclidean assumption. We evaluate the consequences of not accounting for movement heterogeneity when estimating abundance in highly structured landscapes, and demonstrate the value of this approach for estimating biologically realistic space-use patterns and landscape connectivity. We simulated SCR data in a riparian habitat network, using the ecological distance model under a range of scenarios where space-use in and around the landscape was increasingly associated with water (i.e. increasingly less Euclidean). To assess the influence of miscalculating distance on estimates of population size, we compared the results from the ecological and Euclidean distance based models. We then demonstrate that the ecological distance model can be used to estimate home range geometry when space use is not symmetrical. Finally, we provide a method for calculating landscape connectivity based on modelled species-landscape interactions generated from capture-recapture data. Using ecological distance always produced unbiased estimates of abundance. Explicitly modelling the strength of the species-landscape interaction provided a direct measure of landscape connectivity and better characterised true home range geometry. Abundance under the Euclidean distance model was increasingly (negatively) biased as space use was more strongly associated with water and, because home ranges are assumed to be symmetrical, produced poor characterisations of home range geometry and no information about landscape connectivity. The ecological distance SCR model uses spatially indexed capture-recapture data to estimate how activity patterns are influenced by landscape structure. As well as reducing bias in estimates of abundance, this approach provides biologically realistic representations of home range geometry, and direct information about species-landscape interactions. The incorporation of both structural (landscape) and functional (movement) components of connectivity provides a direct measure of species-specific landscape connectivity.

Methods in Ecology and Evolution↗

USGS2008

Ecological effects of large fires on US landscapes: benefit or catastrophe?

The perception is that today’s large fires are an ecological catastrophe because they burn vast areas with high intensities and severities. However, little is known of the ecological impacts of large fires on both historical and contemporary landscapes. The present paper presents a review of the current knowledge of the effects of large fires in the United States by important ecosystems written by regional experts. The ecosystems are (1) ponderosa pine–Douglas-fir, (2) sagebrush–grasslands, (3) piñon–juniper, (4) chaparral, (5) mixed-conifer, and (6) spruce–fir. This review found that large fires were common on most historical western US landscapes and they will continue to be common today with exceptions. Sagebrush ecosystems are currently experiencing larger, more severe, and more frequent large fires compared to historical conditions due to exotic cheatgrass invasions. Historical large fires in south-west ponderosa pine forest created a mixed severity mosaic dominated by non-lethal surface fires while today’s large fires are mostly high severity crown fires. While large fires play an important role in landscape ecology for most regions, their importance is much less in the dry piñon–juniper forests and sagebrush–grasslands. Fire management must address the role of large fires in maintaining the health of many US fire-dominated ecosystems.

International Journal of Wildland Fire↗