Geology topics
Source-linked reports with geographic coverage including western United States.
The recent SnowEx campaign and the new NISAR satellite mission are lighting the way to high-resolution snowpack monitoring and improved decisionmaking in critical river basins around the world.
Fire and drought are expected to increase in frequency and severity in temperate forests due to climate change. To evaluate whether drought increases the likelihood of post-fire tree mortality, we used a large database of tree survival and mortality from 32 years of wildland fires covering four dominant western North American conifers. We used Bayesian hierarchical modeling to predict the probability of individual tree mortality after fire based on species— Pinus contorta (lodgepole pine), Abies concolor (white fir), Pseudotsuga menziesii (Douglas-fir), and Pinus ponderosa (ponderosa pine)—bark thickness, bark char, percentage live tree crown scorched or consumed crown volume scorch (CVS), and mean annual climatic water deficit (CWD) anomalies the year pre-fire and fire year relative to the 1985–2015 reference period. Although crown injury was the primary determinant of tree mortality after fire, drought increased likelihood of death, with a 2-SD increase in CWD (+115.7) resulting in a 78% increase in the probability of mortality. We assessed the crown scorch level expected to result in >50% probability of mortality under different CWD scenarios: observed CWD, CWD of +2, and +4°C warming scenarios. Increased climatic moisture stress amplified tree death, reducing the threshold that causes tree mortality across all conifers under +4°C warming, with more subtle and species-specific reductions for the +2°C scenario. Models predicting post-fire tree mortality are components of global and regional carbon estimates, habitat suitability assessments, and forest management planning and decision support systems. The amplifying effects of drought on post-fire tree mortality and predicted future climates are likely to lead to higher tree mortality following fires in forested landscapes of western North America and may have cascading effects on ecosystem services and future forest resilience.
Recent trends of rising temperatures and longer droughts between precipitation events are impacting water-limited dryland ecosystems in the western United States. Although ecosystem drought response depends directly on soil moisture, trends in soil moisture (e.g., edaphic drought) remain more poorly explored than precipitation (e.g., meteorological drought), representing an important knowledge gap. Here, we applied the SOILWAT2 ecosystem water balance model to quantify long-term trends of soil moisture and edaphic drought using observed daily weather from 1976 to 2019 at 337 stations across the western United States. We assessed edaphic drought for different plant community types (grass dominated vs. shrub dominated), and explored variations with soil depth and texture. The duration of the longest edaphic drought in a given year increased by 1.5 ± 0.2 days/decade for grassy and 1.7 ± 0.2 days/decade for woody vegetation. Importantly, these trends in edaphic drought were consistent with but greater in magnitude compared with meteorological drought indicating more severe water stress for both plants and ecosystems. The correlation between meteorological drought and edaphic drought was greater under woody vegetation (0.45) compared with grass (0.34) and greater at surface soil depths (0–20 cm; 0.46) compared with the deeper soil (20–100 cm; 0.34). Among soil textures, the correlation between meteorological and edaphic drought was highest on sandy soils and lowest on finer textured silty soils. Using the biogeographic domains (eight western NEON domains), we found that the Pacific Northwest, Pacific Southwest, and Desert Southwest exhibited the strongest increases in edaphic drought through time, but lower correlation between meteorological and edaphic droughts. These findings characterize strong but variable connections between edaphic drought and meteorological drought across the western United States and demonstrate the critical influences of vegetation type, soil depth, and soil properties in mediating the magnitude and spatial distribution of edaphic drought.
In water-limited dryland ecosystems of the Western United States, climate change is intensifying the impacts of heat, drought, and wildfire. Disturbances often lead to increased abundance of invasive species, in part, because dryland restoration and rehabilitation are inhibited by limited moisture and infrequent plant recruitment events. Information on ecological resilience to disturbance (recovery potential) and resistance to invasive species can aid in addressing these challenges by informing long-term restoration and conservation planning. Here, we quantified the impacts of projected future climate on ecological resilience and invasion resistance (R&R) in the sagebrush region using novel algorithms based on ecologically relevant and climate-sensitive predictors of climate and ecological drought. We used a process-based ecohydrological model to project these predictor variables and resulting R&R indicators for two future climate scenarios and 20 climate models. Results suggested widespread future R&R decreases (24%–34% of the 1.16 million km 2 study area) that are generally consistent among climate models. Variables related to rising temperatures were most strongly linked to decreases in R&R indicators. New continuous R&R indices quantified responses to climate change; particularly useful for areas without projected change in the R&R category but where R&R still may decrease, for example, some of the areas with a historically low R&R category. Additionally, we found that areas currently characterized as having high sagebrush ecological integrity had the largest areal percentage with expected declines in R&R in the future, suggesting continuing declines in sagebrush ecosystems. One limitation of these R&R projections was relatively novel future climatic conditions in particularly hot and dry areas that were underrepresented in the training data. Including more data from these areas in future updates could further improve the reliability of the projections. Overall, these projected future declines in R&R highlight a growing challenge for natural resource managers in the region, and the resulting spatially explicit datasets provide information that can improve long-term risk assessments, prioritizations, and climate adaptation efforts.
Expansions in the extent and infestation levels of exotic annual grass (EAG) within the rangelands of the western United States are well documented. Land managers are tasked with developing plans to limit EAG spread and prevent irreversible ecosystem deterioration. The most common EAG species and the subject of extensive study is Bromus tectorum (cheatgrass). Cheatgrass has spread rapidly in western rangelands since its initial invasion more than 100 years ago. Another concerning aggressive EAG, Taeniatherum caput-medusae (medusahead), is also commonly found in some of these areas. To control the spread of EAGs, researchers have investigated applying several control methods during different developmental stages of cheatgrass and medusahead. These control strategies require accurate maps of the timing and spatial patterns of the developmental stages to apply mitigation strategies in the correct areas at the right time. In this study, we developed annual phenological datasets for cheatgrass and medusahead with two objectives. The first objective was to determine if cheatgrass and medusahead can be differentiated at 30 m resolution using their phenological differences. The second objective was to establish an annual phenology metric regression tree model used to map the growing seasons of cheatgrass and medusahead. Harmonized Landsat and Sentinel-2 (HLS)-derived predicted weekly cloud-free 30 m normalized difference vegetation index (NDVI) images were used to develop these metric maps. The result of this effort was maps that identify the start and end of sustained growing season time for cheatgrass and medusahead at 30 m for the Snake River Plain and Northern Basin and Range ecoregions. These phenological datasets also identify the start and end-of-season NDVI values, along with maximum NDVI throughout the study period. These metrics may be utilized to characterize annual growth patterns for cheatgrass and medusahead. This approach can be utilized to plan time-sensitive control measures such as herbicide applications or cattle grazing.
Broadly distributed across the Western United States, ungulates (hooved mammals) play an important role in ecosystem function by affecting vegetation communities and forming the prey base for large carnivores. Additionally, ungulates provide economic benefits to regional communities through tourism and hunting and hold cultural significance for many Tribal communities. Many ungulates migrate seasonally between distinct summer and winter ranges to take advantage of spatially and temporally variable food sources and avoid threats such as predators and deep snow. Increasingly, these migrations are threatened by the growing human footprint and associated subdivisions, energy development, and increased traffic volume. Efforts to study ungulate populations and conserve their migrations received support in recent years from the U.S. Department of the Interior Secretarial Order No. 3362, which provided Federal support for enhancing habitat quality for ungulates across the Western States. In response to Secretarial Order No. 3362, the U.S. Geological Survey (USGS) established the Corridor Mapping Team, a collaboration among USGS and participating State and Federal wildlife management agencies and numerous Tribal Nations. Together, the Corridor Mapping Team maps ungulate migrations throughout the Western United States in the USGS “Ungulate Migrations of the Western United States” report series. This report (volume 4) details migrations and seasonal ranges from 31 new herds throughout nine Western States. Additionally, this report includes updates to two herds published in previous reports. Including this report, the report series has provided the mapped migrations and seasonal ranges of 182 unique herds and has provided a map-based inventory of the documented ungulate migrations across the Western United States for biologists, managers, policy makers, and conservation practitioners. This report also discusses how the mapping efforts associated with the Corridor Mapping Team can be used to guide management and policy regarding renewable energy development and ungulate disease, specifically chronic wasting disease, in the Western United States.
Paciorek and Wehner raise important questions around our use of the Mann-Kendall nonparametric trend test on smoothed data for analyzing long-term hydrometeorological trends in Zhang et al. (2021, https://doi.org/10.1029/2020gl092293 ). We thank them for initiating this important conversation and their gracious cooperation in exploring the issues addressed in their comment. In this reply we confirm the inflation of significant p -values by our choice to smooth, illustrate the relatively minor impacts on the main conclusions of our paper, and add our voices to those of Paciorek and Wehner in highlighting the lack of methodology for hypothesis testing across multiple stations that have spatial structure (i.e., testing for regionally consistent trends).
The global prevalence of mercury (Hg) contamination and its complex biogeochemical cycling has resulted in elevated Hg concentrations in biota in remote and pristine environments. However, there is uncertainty in the relative importance of Hg deposition and landscape factors that control Hg cycling and bioaccumulation. To address this, we measured total mercury (THg) concentrations in 1344 fish across 60 subalpine lakes from 12 national parks (NPs). These parks represent three distinct high-elevation regions across the western U.S.: Cascades and Olympic Peninsula, Sierra Nevada and Great Basin, and Rocky Mountains. Within these regions, three NPs (Mount Rainier, Yosemite, and Rocky Mountain) were intensively studied representatives of each region. This study aimed to (1) assess the magnitude of mercury contamination in a collection of remote, small catchment lakes; (2) quantify the variability of fish THg concentrations among and within parks; and (3) test the relative importance of Hg inputs in comparison to landscape characteristics on lake-specific fish THg concentrations. The spatial variability in fish THg concentrations was 2.6-fold higher than variation in deposition to watersheds, suggesting that factors other than Hg delivery are important determinants of Hg accumulation in these environments. Spatially, fish THg concentrations (ng/g ww ± standard error) were lower in the Rockies (46.2 ± 5.0) and Sierra (56.5 ± 5.8) compared to the Cascades (67.8 ± 6.1). Additionally, fish THg concentrations increased with increasing conifer forest cover (Intensive parks: P < 0.0001, R 2 = 0.43; All parks: P = 0.0001, R 2 = 0.23) but were not correlated with wet Hg deposition across the catchment. These findings suggest that forest composition is likely an important aspect of Hg delivery to lake food webs, and although the mechanisms are unclear, could be tied to some combination of forest influences on catchment organic carbon and increased surface area for dry Hg deposition.
The El Niño Southern Oscillation (ENSO) in the tropical Pacific Ocean is an important driver of winter precipitation variability over western North America as a whole, but ENSO exhibits a weak and inconsistent relationship with precipitation in several critically important headwaters including the upper Colorado River Basin. We present interactions between North Atlantic sea surface temperatures (SSTs) and ENSO that influence western U.S. precipitation, accounting for substantial variability in areas where ENSO alone yields limited guidance. Specifically, we performed a statistical analysis on hemispheric SSTs and western U.S. winter precipitation in a century of observations and a 10,000-year perpetual current-climate simulation. In both frameworks, the leading coupled pattern is ENSO, and the second pattern links an Atlantic Quadpole Mode (AQM) of SST variability to precipitation anomalies over most of the western U.S., including the transition zone where ENSO provides little predictability. The AQM SST anomalies are expansive in latitude, but its primary mechanism appears to involve a strengthening/shifting of the intertropical convergence zone (ITCZ) over northern South America and the tropical Atlantic. The ENSO pattern accounts for a larger fraction of the total covariance between SSTs and precipitation (65% versus 12% for the AQM pattern), but the percent anomalies of precipitation associated with ENSO and the AQM are comparable in magnitude, meaning 20% or larger over much of the western U.S. The interaction between ENSO and AQM influences precipitation across the western U.S., with cold AQM generally reducing precipitation irrespective of ENSO whereas warm AQM increases the amount of precipitation and the area of influence of ENSO; knowledge of these interactions can increase predictability of western U.S. precipitation.
Conserving genetic connectivity is fundamental to species persistence, yet rarely is made actionable into spatial planning for imperilled species. Climate change and habitat degradation have added urgency to embrace connectivity into networks of protected areas. Our two-step process integrates a network model with a functional connectivity model, to identify population centres important to maintaining genetic connectivity then to delineate those pathways most likely to facilitate connectivity thereamong for the greater sage-grouse ( Centrocercus urophasianus ), a species of conservation concern ranging across eleven western US states and into two Canadian provinces. This replicable process yielded spatial action maps, able to be prioritized by importance to maintaining range-wide genetic connectivity. We used these maps to investigate the efficacy of 3.2 million ha designated as priority areas for conservation (PACs) to encompass functional connectivity. We discovered that PACs encompassed 41.1% of cumulative functional connectivity—twice the amount of connectivity as random—and disproportionately encompassed the highest-connectivity landscapes. Comparing spatial action maps to impedances to connectivity such as cultivation and woodland expansion allows both planning for future management and tracking outcomes from past efforts.
Loss and degradation of sagebrush rangelands due to an accelerated invasive annual grass-wildfire cycle and other stressors are significant management, conservation, and economic issues in the western United States. These sagebrush rangelands comprise a unique biome spanning 11 states, support over 350 wildlife species, and provide important ecosystem services that include stabilizing the economies of western communities. Impacts to sagebrush ecosystem processes over large areas due to the annual grass-wildfire cycle necessitated the development of a coordinated, science-based strategy for improving efforts to achieve long-term protection, conservation, and restoration of sagebrush rangelands, which was framed in 2015 under the Integrated Rangeland Fire Management Strategy (IRFMS). Central to this effort was the development of an Actionable Science Plan (Plan) that identified 37 priority science needs (Needs) for informing the actions proposed under the 5 topics (Fire, Invasives, Restoration, Sagebrush and Sage-Grouse, Climate and Weather) that were part of the collective focus of the IRFMS. Notable keys to this effort were identification of the Needs co-produced by managers and researchers, and a focus on resulting science being “actionable.” Substantial investments aimed at fulfilling the Needs identified in the Plan have been made since its release in 2016. While the state of the science has advanced considerably, the extent to which knowledge gaps remain relative to identified Needs is relatively unknown. Moreover, new Needs have likely emerged since the original strategy as results from actionable science reveal new questions and possible (yet untested) solutions. A quantifiable assessment of the progress made on the original science Needs can identify unresolved gaps and new information that can help inform prioritization of future research efforts. This report details a systematic literature review that evaluated how well peer-reviewed journal articles and formal technical reports published between January 1, 2015, and December 31, 2020, addressed six needs (hereinafter “Needs”) identified under the Invasives topic in the Plan. The topic outlined research Needs related to the control of invasive plant species in sagebrush rangelands, with a special emphasis on invasive annual grasses. We established the level of progress towards addressing each Need following a standardized set of criteria, and developed summaries detailing how research objectives nested within Needs identified in the Plan (“Next Steps”) were either addressed well, partially addressed, or remain outstanding (that is, addressed poorly) in the literature through 2020. Our searches resulted in the inclusion of 198 science products that at least partially addressed a Need identified in the Invasives topic. The Needs that were well and partially addressed included: studies of natural and anthropogenic factors influencing the distribution and spread; methods of preventing, eradicating and controlling invasive plant species; development of mapping techniques that provide regularly updated annual grass and fine fuel projections; and assessment of the efficacy of potential cheatgrass biocontrol agents. Needs that were addressed poorly included (1) investigations of livestock grazing as a tool for managing invasive plants and (2) investigations of cheatgrass die-offs and identification and subsequent study of potential biocontrol agents associated with those die-offs. The information provided in this assessment will assist updating the Plan along with other science strategies.
Loss and degradation of sagebrush rangelands due to an accelerated invasive annual grass-wildfire cycle and other stressors are substantial management, conservation, and economic issues in the western United States. These sagebrush rangelands comprise a unique biome spanning 11 states, support over 350 wildlife species, and provide important ecosystem services that include stabilizing the economies of western communities. Impacts to sagebrush ecosystem processes over large areas due to the annual grass-wildfire cycle necessitated the development of a coordinated, science-based strategy for improving efforts to achieve long-term protection, conservation, and restoration of sagebrush rangelands, which was framed in 2015 under the Integrated Rangeland Fire Management Strategy (IRFMS). Central to this effort was the development of an Actionable Science Plan (Plan) that identified 37 priority science needs (Needs) for informing the actions proposed under the 5 topics (Fire, Invasives, Restoration, Sagebrush and Sage-Grouse, Climate and Weather) that were part of the collective focus of the IRFMS. Notable keys to this effort were identification of the Needs co-produced by managers and researchers, and a focus on resulting science being “actionable.” Substantial investments aimed at fulfilling the Needs identified in the Plan have been made since its release in 2016. While the state of the science has advanced considerably, the extent to which knowledge gaps remain relative to identified Needs is relatively unknown. Moreover, new Needs have likely emerged since the original strategy as results from actionable science reveal new questions, and possible (yet untested) solutions. A quantifiable assessment of the progress made on the original science Needs can identify unresolved gaps and new information that can help inform prioritization of future research efforts. This report details a systematic literature review that evaluated how well peer-reviewed journal articles and formal technical reports published between January 1, 2015, and December 31, 2020, addressed 10 needs (hereinafter “Needs”) identified under the Restoration topic in the Plan. The topic outlined research Needs for improving restoration success in degraded sagebrush rangelands. We established the level of progress towards addressing each Need following a standardized set of criteria, and developed summaries detailing how research objectives nested within Needs identified in the Plan (“Next Steps”) were either addressed well, partially addressed or remain outstanding (that is, addressed poorly) in the literature through 2020. Our searches resulted in the inclusion of 371 science products that at least partially addressed a Need identified in the Restoration topic. The Needs that were well and partially addressed included: the development of methods to improve seeding success of native plants after fire; evaluation of short- and long-term plant responses relative to biotic and abiotic factors following restoration treatments; assessments of long-term effects on ecosystem processes following conifer removal treatments and development of decision support tools to aid in conifer management; determination of the costs of restoration treatments relative to the benefits to sage-grouse occupancy, survival, and populations; and assessments of the factors which contribute to soil degradation and development of soil enhancement methods that enhance seed germination and seedling survival while resisting nonnative plants. Needs that were not addressed well included: the development of methods for the rapid recovery of sagebrush and native herbaceous plants following wildfire and determination of whether treatments benefit sage-grouse and mitigate impacts from fires; determination of thresholds for successful restoration across a range of environmental conditions and development of decision support tools to assist with restoration effectiveness monitoring; and development and evaluation of the utility of seed transfer zones. The information provided in this assessment will assist updating the Plan along with other science strategies.
Loss and degradation of sagebrush rangelands due to an accelerated invasive annual grass-wildfire cycle and other stressors are significant management, conservation, and economic issues in the western United States. These sagebrush rangelands comprise a unique biome spanning 11 states, support over 350 wildlife species, and provide important ecosystem services that include stabilizing the economies of western communities. Impacts to sagebrush ecosystem processes over large areas due to the annual grass-wildfire cycle necessitated the development of a coordinated, science-based strategy for improving efforts to achieve long-term protection, conservation, and restoration of sagebrush rangelands, which was framed in 2015 under the Integrated Rangeland Fire Management Strategy (IRFMS). Central to this effort was the development of an Actionable Science Plan (Plan) that identified 37 priority science needs (Needs) for informing the actions proposed under the 5 topics (Fire, Invasives, Restoration, Sagebrush and Sage-Grouse, Climate and Weather) that were part of the collective focus of the IRFMS. Notable keys to this effort were identification of the Needs co-produced by managers and researchers, and a focus on resulting science being “actionable.” Substantial investments aimed at fulfilling the Needs identified in the Plan have been made since its release in 2016. While the state of the science has advanced considerably, the extent to which knowledge gaps remain relative to identified Needs is relatively unknown. Moreover, new Needs have likely emerged since the original strategy as results from actionable science reveal new questions and possible (yet untested) solutions. A quantifiable assessment of the progress made on the original science Needs can identify unresolved gaps and new information that can help inform prioritization of future research efforts. This report details a systematic literature review that evaluated how well peer-reviewed journal articles and formal technical reports published between January 1, 2015, and December 31, 2020, addressed eight needs (hereinafter known as “Needs”) identified under the Fire topic in the Plan, defined as any non-structure fire that occurs in vegetation or natural fuels, including wildfires and prescribed fires. The topic outlined research Needs broadly focused on understanding the mechanisms and management of threats posed to the maintenance of large, contiguous sagebrush rangelands by fire. We established the level of progress towards addressing each Need following a standardized set of criteria, and developed summaries detailing how research objectives nested within Needs identified in the Plan (‘Next Steps’) were either addressed well, partially addressed or remain outstanding (in other words., addressed poorly) in the literature through 2020. Our searches resulted in the inclusion of 156 science products that at least partially addressed a Need identified in the Fire topic. The Needs that were well and partially addressed included: studies of relationships between fire and the sagebrush ecosystem (Need 1) investigations of the responses of sage-grouse to burned area characteristics (Need 2); spatial modeling of fire risk (Need 3); studies of the effects of fuels management treatments (Need 4); sagebrush reduction treatments on multiple characteristics of the sagebrush ecosystem (Need 6); and assessments of the role of fire in maintaining healthy sagebrush communities (Need 7). Needs addressed poorly included: assessments of the effects of fuel breaks on sage-grouse (Need 5); and investigations of characteristics associated with the effectiveness of fuel breaks (Need 8). The information provided in this assessment will assist updating the Plan along with other science strategies.
Loss and degradation of sagebrush rangelands due to an accelerated invasive annual grass-wildfire cycle and other stressors are significant management, conservation, and economic issues in the western United States. These sagebrush rangelands comprise a unique biome spanning 11 states, support over 350 wildlife species, and provide important ecosystem services that include stabilizing the economies of western communities. Impacts to sagebrush ecosystem processes over large areas due to the annual grass-wildfire cycle necessitated the development of a coordinated, science-based strategy for improving efforts to achieve long-term protection, conservation, and restoration of sagebrush rangelands, which was framed in 2015 under the Integrated Rangeland Fire Management Strategy (IRFMS). Central to this effort was the development of an Actionable Science Plan (Plan) that identified 37 priority science needs (Needs) for informing the actions proposed under the 5 topics (Fire, Invasives, Restoration, Sagebrush and Sage-Grouse, Climate and Weather) that were part of the collective focus of the IRFMS. Notable keys to this effort were identification of the Needs co-produced by managers and researchers, and a focus on resulting science being “actionable.” Substantial investments aimed at fulfilling the Needs identified in the Plan have been made since its release in 2016. While the state of the science has advanced considerably, the extent to which knowledge gaps remain relative to identified Needs is relatively unknown. Moreover, new Needs have likely emerged since the original strategy as results from actionable science reveal new questions and possible (yet untested) solutions. A quantifiable assessment of the progress made on the original science Needs can identify unresolved gaps and new information that can help inform prioritization of future research efforts. This report details a systematic literature review that evaluated how well peer-reviewed journal articles and formal technical reports published between January 1, 2015, and December 31, 2020, addressed nine needs (hereinafter, “Needs”) identified under the Sagebrush and Sage-Grouse topic in the Plan. The topic outlined research Needs broadly focused on understanding sagebrush rangelands and population dynamics important for the conservation and management of sage-grouse and other sagebrush-reliant wildlife species. We established the level of progress towards addressing each Need following a standardized set of criteria, and developed summaries detailing how research objectives nested within Needs identified in the Plan (‘Next Steps’) were either addressed well, partially addressed or remain outstanding (in other words, addressed poorly) in the literature through 2020. Our searches resulted in the inclusion of 333 science products that at least partially addressed a Need identified in the Sagebrush and Sage-Grouse topic. The Needs that were well and partially addressed included: development of biome-wide mapping techniques that provide regularly updated grassland and shrubland vegetation layers (Need 4); generation of spatially explicit greater sage-grouse habitat suitability and population models (Need 5); identification of greater sage-grouse seasonal habitats (Need 6); identification of thresholds for the extent of threats, especially conifer expansion, above which greater sage-grouse and other sagebrush-obligate species cannot persist (Need 8); and studies of sagebrush community dynamics as those relate to management and restoration of sagebrush rangelands (Need 9). Needs addressed poorly included: investigations of factors conducive and restrictive to greater sage-grouse movement patterns and population connectivity (Need 1); investigations of livestock and other large ungulate (for example, feral horse) grazing effects on greater sage-grouse populations and habitats (Need 2); identification of thresholds of disturbance (especially renewable energy developments) below which greater sage-grouse and other sagebrush reliant species are not impacted (Need 3); and studies of habitat relationships for sagebrush-reliant species other than greater sage-grouse, songbirds, and small mammals (Need 7). The information provided in this assessment will assist updating the Plan along with other science strategies.
The Rangeland Condition Monitoring Assessment and Projection (RCMAP) project quantifies the percentage cover of rangeland components across the western United States using Landsat imagery from 1985 to 2021. The RCMAP product suite consists of nine fractional components: annual herbaceous, bare ground, herbaceous, litter, nonsagebrush shrub, perennial herbaceous, sagebrush, shrub, and tree, in addition to the temporal trends of each component. Several enhancements were made to the RCMAP process relative to prior generations. First, we have trained time-series predictions directly from 331 high-resolution sites collected from 2013 to 2018 and additional field data; for example, Bureau of Land Management Assessment, Inventory, and Monitoring instead of using the 2016 “base” map as an intermediary. This removes one level of model error and allows the direct association of high-resolution derived training data to the corresponding year of Landsat imagery. Neural network models have replaced Cubist models as our classifier. Continuous Change Detection and Classification synthetic Landsat images were obtained for six monthly periods for each region and were added as predictors. These data enhance the phenologic detail of imagery, improving discrimination among components. Postprocessing has been improved with updated fire recovery equations stratified by ecosystem resistance and resilience classes. Additionally, postprocessing has been enhanced through a revised noise detection model, based on third order polynomial models for each component and each pixel. These data can be used to answer critical questions regarding the effect of climate change and the suitability of management practices. Component products can be downloaded from the Multi-Resolution Land Characteristics Consortium website at https://www.mrlc.gov/data .
Predicting species geographic distributions is key to managing invasive species, conserving biodiversity, and understanding species' environmental requirements. Species distribution models (SDMs) commonly focus on climatic predictors, but other environmental factors can also be essential, particularly for species with specialized habitats defined by hydrologic, topographic, or edaphic conditions (e.g., riparian, wetland, alpine, coastal, serpentine). Here, we demonstrate a novel approach for capturing strong effects of both hydrologic and climatic predictors in SDMs for riparian plants, by merging analyses targeted at environmental drivers within riparian ecosystems and across the western USA (3.8 × 10 6 km 2 ). We developed presence-background SDMs from five algorithms for three invasive riparian trees ( Tamarix ramossisima / chinensis [saltcedar], Elaeagnus angustifolia [Russian olive], and Ulmus pumila [Siberian elm]) and three native Populus spp. (cottonwoods). We used separate background datasets to develop models with different spatial scales of inference: (1) spatially filtered random points to represent available habitat across the study area and (2) target-group points from Salix (willow) occurrences to represent available riparian habitat. Random-background models captured hydrologic drivers of riparian tree distributions relative to the largely upland western USA, whereas Salix -background models captured climatic drivers within the context of riparian ecosystems. Combining predictions from the two backgrounds identified hydrologically suitable habitats within climatically suitable regions, resulting in fewer false “absences” than either background alone, improving predictions over previous SDMs, and providing more complete information to guide management decisions. Surprisingly, the predicted habitat for U. pumila , a newly recognized riparian invader, was as or more extensive than Populus deltoides / fremontii , T. ramossisima / chinensis , and E. angustifolia , the most common riparian tree complexes in the western USA. Watersheds constituting 20% of U. pumila predicted habitat contained no occurrence records, indicating high risk of future and unrecognized invasions. Combining models from random and ecosystem-specific target-group backgrounds may improve SDMs for species from many specialized habitats, providing a method to link predicted distributions to localized geographic features while capturing broad-scale climatic requirements.
A key uncertainty of empirical models of post-fire tree mortality is understanding the drivers of elevated post-fire mortality several years following fire, known as delayed mortality. Delayed mortality can represent a substantial fraction of mortality, particularly for large trees that are a conservation focus in western US coniferous forests. Current post-fire tree mortality models have undergone limited evaluation of how injury level and time since fire interact to influence model accuracy and predictor variable importance. Less severe injuries potentially serve as an indicator for vulnerability to additional stressors such as bark beetle attack or moisture stress. We used a collection of 164,293 individual tree records to examine post-fire tree mortality in eight western USA conifers: Abies concolor , A. grandis , Calocedrus decurrens , Larix occidentalis , Pinus contorta , P. lambertiana , P. ponderosa , and Pseudotsuga menziesii . We evaluated the importance of fire injury predictors on discriminating between surviving trees versus immediate and delayed post-fire mortality. We fit balanced random forest models for each species using cumulative tree mortality from 1–5-years post-fire. We compared these results to multi-class random forest models using first-year mortality, 2–5-year mortality, and survival 5-years post-fire as a response variable. Crown volume scorched, diameter at breast height, and relative bark char height, were used as predictor variables. The cumulative mortality models all predicted trees that died within 1-year of fire with high accuracy but failed to predict 2–5-year mortality. The multi-class models were an improvement but had lower accuracy for predicting 2–5-year mortality. Multi-class model accuracies ranged from 85–95% across all species for predicting 1-year post-fire mortality, 42–71% for predicting 2–5-year mortality, and 64–85% for predicting trees that lived past 5-years. Our study highlights the differences in tree species tolerance to fire injury and suggests that including second-order predictors such as beetle attack or climatic water stress before and after fire will be critical to improve accuracy and better understand the mechanisms and patterns of fire-caused tree death. Random forest models have potential for management applications such as post-fire harvesting and simulating future stand dynamics.
We present a model of the lower seismogenic depth of earthquakes in the western United States (WUS) estimated using the hypocentral depths of events M > 1, a crustal temperature model, and historical earthquake rupture depth models. Locations of earthquakes are from the Advanced National Seismic System Comprehensive Earthquake Catalog from 1980 to 2021 supplemented with seismicity in southern California for event hypocenters that were relocated by Hauksson et al. (2012) to obtain higher precision and better resolution in the model. We calculated the average depth of the deepest 10% of the merged catalog using an adaptive radius of 50 km or more. Along the San Andreas fault, the deepest seismogenic depths are located at 23 km around the Cholame segment, whereas the shallowest depths are located at about 10 km along the Rodgers Creek and Maacama faults. For the WUS outside California, the depth generally varies between 10 and 25 km with an average around 14 km but could extend to 35 km along Cascadia subduction zone. We find good agreement between the small‐magnitude depths and rupture depths derived from coseismic slip of large earthquakes across the region. Our estimates are generally deeper than the previous seismogenic depths determined for the Uniform California Earthquake Rupture Forecast, Version 3 model based on work by Petersen et al. (1996) who used seismicity cross sections along major fault zones in California. Our new seismogenic depth distribution correlates closely with crustal temperature derived from WUS heat flow ( Blackwell et al. , 2011 ). This correlation allowed us to develop a map of the brittle–ductile transition that we use to replace seismogenic depths in the model east of the Intermountain West Seismic Belt where the seismicity rate is low. This updated depth model is useful for recalibrating the lower geologic fault rupture depths, and constraining deformation and seismicity source models in updates of the U.S. Geological Survey National Seismic Hazard Model.