Search Results (16)

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. Full article

Two species of Psilochalcis wasps (P. minuta and P. quadratis) were recently described from Utah’s eastern Great Basin. The extent of their known distributions is extremely limited, based on few data points. We developed species distribution models (SDMs) using Maxent modeling software for each Psilochalcis species to identify areas of probable suitable habitat for targeted collecting to improve our knowledge of their distributions. We used six occurrence data points for P. minuta and eight occurrence data points for P. quadratis, along with ten environmental variables as inputs into the Maxent modeling software. Model-predicted areas with a potential suitable habitat value greater than 0.69 were mapped using ArcGIS Pro to help select locations for model accuracy assessment. Employing Malaise traps, eighteen sites were sampled to evaluate each SDM’s ability to predict the occurrence of Psilochalcis species. Psilochalcis minuta occurred at eight of nine juniper-dominated sample sites that were predicted as having high suitability by the model for this species. Likewise, P. quadratis occurred at two of four cheatgrass-dominated sample sites predicted by the model. Psilochalcis minuta occurred at three of nine sampled sites that were not predicted by the model, and P. quadratis occurred at seven of fourteen non-predicted sites. The Maxent SDM results yielded an AUC value of 0.70 and p-value of 0.02 for P. minuta and 0.68 and 0.02. for P. quadratis. These results were reflected in our model accuracy assessment. Of the selected environmental variables, aspect, historic fire disturbance, and elevation yielded the greatest percent contributions to both species’ models. Sympatric distributions were observed for P. minuta and P. quadratis. Elevation, vegetation type, NDVI, and soil type are the most important environmental variables in differentiating areas of optimal suitable habitat for the two species. Full article

Two species of Psilochalcis (Hymenoptera: Chalcididae) wasps occurring in the Great Basin region of the western United States were sampled from three locations in central Utah (USA) over a two-year period using Malaise traps. Each location is composed of four contiguous habitat types: pinyon/juniper (Pinus edulis or P. monophylla and Juniperus osteosperma), sagebrush (Artemisia tridentata), cheatgrass (Bromus tectorum), and crested wheatgrass (Agropyron cristatum). Seasonal trap abundance for each Psilochalcis species was determined. Psilochalcis minuta Petersen and Psilochalcis quadratis Petersen occur in highest abundance from mid-May to early August. Psilochalcis minuta demonstrates a significant association with pinyon/juniper habitat, specifically at the Utah; Juab County, Yuba Valley sample site, whereas P. quadratis demonstrates a significant association with cheatgrass (Bromus tectorum) habitat at the same location. Full article

A new species of eriophyoid mite, Aculodes marcelli sp. nov., was discovered on cheatgrass, Anisantha tectorum (L.) Nevski (syn. Bromus tectorum L.), an annual grass that is native to Eurasia and Northern Africa. This grass was introduced to North America near the end of the 19th century and now is widespread and associated with the observed increases in the size, frequency, and intensity of wildfires in western N. America. In this paper, A. marcelli sp. nov., is morphologically described and illustrated. Compared with other Aculodes spp., it differs based on morphology and the sequence of the mitochondrial cytochrome oxidase gene, subunit I (MT-CO1). Results of morphometric analysis showed clear differentiation between A. marcelli sp. nov., and the most similar congener, A. altamurgiensis from Taeniatherum caput-medusae. Analysis of MT-CO1 sequence divergence revealed significant levels of genetic variation (17.7%) and supported the results from the morphometric analysis; therefore, it is determined that they are two different species. Aculodes marcelli sp. nov., is a new candidate agent for classical biological control of A. tectorum. Full article

A bulldozed fire line is a fire-suppression technique that limits fire movement by altering fuel continuity through vegetation removal and mineral soil exposure. The ecological impacts of a bulldozed fire line may exceed the effects of the fire itself through lasting changes in the soil and vegetation properties; however, little research has been performed to quantify these impacts in grassland systems. In this study, we compared vegetation properties among burned, unburned, and bulldozed fire line conditions on two August 2012 grassland wildfires in Montana. Standing biomass, by growth form, was quantified in 2013 and 2014, and compared using a generalized linear model. Perennial grass production was significantly reduced, while annual grass and annual forb biomass increased in response to the fire line treatment. Shrub and total vegetation standing crop were reduced in response to the fire line in 2013; however, the treatment effects were diminished by 2014. The burned and unburned treatments were generally similar within two years post-fire. The loss of perennial grasses and invasion of competitive annual grasses such as cheatgrass (Bromus tectorum L.) may limit the vegetation recovery of the fire line and promote further invasion of annual grasses into these systems. The marginal impact of the fires on these plant communities suggests the need to limit the use of ad hoc bulldozed fire lines as a suppression activity. If a bulldozed fire line is constructed, we suggest limiting soil disturbance by restricting blade depth to remove only surface vegetation and restricting bulldozer use to flat slopes, even if working with the contour, and incorporating re-seeding as part of or immediately after fire line construction. Full article

The invasion of exotic annual grass (EAG), e.g., cheatgrass (Bromus tectorum) and medusahead (Taeniatherum caput-medusae), into rangeland ecosystems of the western United States is a broad-scale problem that affects wildlife habitats, increases wildfire frequency, and adds to land management costs. However, identifying individual species of EAG abundance from remote sensing, particularly at early stages of invasion or growth, can be problematic because of overlapping controls and similar phenological characteristics among native and other exotic vegetation. Subsequently, refining and developing tools capable of quantifying the abundance and phenology of annual and perennial grass species would be beneficial to help inform conservation and management efforts at local to regional scales. Here, we deploy an enhanced version of the U.S. Geological Survey Rangeland Exotic Plant Monitoring System to develop timely and accurate maps of annual (2016–2020) and intra-annual (May 2021 and July 2021) abundances of exotic annual and perennial grass species throughout the rangelands of the western United States. This monitoring system leverages field observations and remote-sensing data with artificial intelligence/machine learning to rapidly produce annual and early season estimates of species abundances at a 30-m spatial resolution. We introduce a fully automated and multi-task deep-learning framework to simultaneously predict and generate weekly, near-seamless composites of Harmonized Landsat Sentinel-2 spectral data. These data, along with auxiliary datasets and time series metrics, are incorporated into an ensemble of independent XGBoost models. This study demonstrates that inclusion of the Normalized Difference Vegetation Index and Normalized Difference Wetness Index time-series data generated from our deep-learning framework enables near real-time and accurate mapping of EAG (Median Absolute Error (MdAE): 3.22, 2.72, and 0.02; and correlation coefficient (r): 0.82, 0.81, and 0.73; respectively for EAG, cheatgrass, and medusahead) and native perennial grass abundance (MdAE: 2.51, r:0.72 for Sandberg bluegrass (Poa secunda)). Our approach and the resulting data provide insights into rangeland grass dynamics, which will be useful for applications, such as fire and drought monitoring, habitat suitability mapping, as well as land-cover and land-change modelling. Spatially explicit, timely, and accurate species-specific abundance datasets provide invaluable information to land managers. Full article

Cheatgrass is an annual grass species from Eurasia that has become invasive in much of western North America. It has been implicated in recent increases in the frequency, size, and intensity of wildfires, contributing to severe economic, environmental, and social destruction. In order to reduce this damage, the USDA-ARS established a classical biological control program against cheatgrass. In 2018 and 2019, adult gall midges were collected emerging from cheatgrass seed heads collected at several sites in Bulgaria and Greece; this is the first gall midge ever recorded from cheatgrass. Morphological comparisons with related midge species recorded from other plant hosts revealed that this midge from cheatgrass is a new species, described here as Stenodiplosis tectori n. sp. This status was supported by sequence comparisons of a barcode region of the gene encoding the mitochondrial cytochrome c subunit I (CO1) protein in Stenodiplosis tectori n. sp. and three congeners. The present study is the first to report MT-CO1 data in the genus Stenodiplosis. The ingroup Stenodiplosis tectori n. sp. collected in the Balkans grouped in one phylogenetic supported clade, with an average K2P-distance from its closest related congener, S. sorghicola, of 7.73% (SD = 1.10). The findings indicated relatively high year-to-year within-population diversity. Implications for this gall midge’s utility as a biological control agent of cheatgrass are discussed. Full article

Cheatgrass (Bromus tectorum) invasion is driving an emerging cycle of increased fire frequency and irreversible loss of wildlife habitat in the western US. Yet, detailed spatial information about its occurrence is still lacking for much of its presumably invaded range. Deep learning (DL) has demonstrated success for remote sensing applications but is less tested on more challenging tasks like identifying biological invasions using sub-pixel phenomena. We compare two DL architectures and the more conventional Random Forest and Logistic Regression methods to improve upon a previous effort to map cheatgrass occurrence at >2% canopy cover. High-dimensional sets of biophysical, MODIS, and Landsat-7 ETM+ predictor variables are also compared to evaluate different multi-modal data strategies. All model configurations improved results relative to the case study and accuracy generally improved by combining data from both sensors with biophysical data. Cheatgrass occurrence is mapped at 30 m ground sample distance (GSD) with an estimated 78.1% accuracy, compared to 250-m GSD and 71% map accuracy in the case study. Furthermore, DL is shown to be competitive with well-established machine learning methods in a limited data regime, suggesting it can be an effective tool for mapping biological invasions and more broadly for multi-modal remote sensing applications. Full article

The impacts of climate change are expected to alter the abundance and distribution of invasive annual grasses, such as Bromus tectorum L. (cheatgrass) and Ventenata dubia (Leers) Coss. (ventenata). High temperature extremes will be more frequent and for longer periods, and increased atmospheric CO₂ is expected to double even with the most conservative estimates. Climate change draws concern for the potential success of winter annual grasses in arid and semi-arid plant communities. Information on B. tectorum’s growth response to climate change in laboratory and field experiments are available for monocultures; however, more knowledge is needed on the response when growing with other invasive grasses, such as V. dubia. We examined differences in seedling growth for V. dubia and B. tectorum growing alone and with each other under current (4 °C/23 °C at 400 ppm CO₂) and elevated (10.6 °C/29.6 °C at 800 ppm CO₂) climate conditions. There was one trial per climate scenario with 10 replications per competition type (inter-, intra-specific competition for each species). Bromus tectorum was larger than V. dubia across climate and competition treatments, but contrary to previous studies, both species were smaller in the elevated climate treatment. Ventenata dubia allocated more growth to its roots than B. tectorum across both climate treatments, indicating V. dubia may have a competitive advantage for soil resources now and in the future. Full article

Woodland encroachment is a global issue linked to diminished ecosystem services, prompting the need for restoration efforts. However, restoration outcomes can be highly variable, making it difficult to interpret the ecological benefits and risks associated with woodland-reduction treatments within semiarid ecosystems. We addressed this uncertainty by assessing the magnitude and direction of vegetation change over a 15-year period at 129 sagebrush (Artemisia spp.) sites following pinyon (Pinus spp.) and juniper (Juniperus spp.) (P–J) reduction. Pretreatment vegetation indicated strong negative relationships between P–J cover and the abundance of understory plants (i.e., perennial grass and sagebrush cover) in most situations and all three components differed significantly among planned treatment types. Thus, to avoid confounding pretreatment vegetation and treatment type, we quantified overall treatment effects and tested whether distinct response patterns would be present among three dominant plant community types that vary in edaphic properties and occur within distinct temperature/precipitation regimes using meta-analysis (effect size = lnRR = ln[posttreatment cover/pretreatment cover]). We also quantified how restoration seedings contributed to overall changes in key understory vegetation components. Meta-analyses indicated that while P–J reduction caused significant positive overall effects on all shrub and herbaceous components (including invasive cheatgrass [Bromus tectorum] and exotic annual forbs), responses were contingent on treatment- and plant community-type combinations. Restoration seedings also had strong positive effects on understory vegetation by augmenting changes in perennial grass and perennial forb components, which similarly varied by plant community type. Collectively, our results identified specific situations where broad-scale efforts to reverse woodland encroachment substantially met short-term management goals of restoring valuable ecosystem services and where P–J reduction disposed certain plant community types to ecological risks, such as increasing the probability of native species displacement and stimulating an annual grass-fire cycle. Resource managers should carefully weigh these benefits and risks and incorporate additional, appropriate treatments and/or conservation measures for the unique preconditions of a given plant community in order to minimize exotic species responses and/or enhance desirable outcomes. Full article

Fire exclusion has dramatically altered historically fire adapted forests across western North America. In response, forest managers reduce forest fuels with mechanical thinning and/or prescribed burning to alter fire behavior, with additional objectives of restoring forest composition, structure, and ecosystem processes. There has been extensive research on the effects of fuel reduction and restoration treatments on trees, fuels, regeneration, and fire behavior; but less is known about how these treatments influence understory vegetation, which contains the majority of vascular plant diversity in many dry conifer forests. Of particular interest is how understory vegetation may respond to the season and interval of prescribed burning. The season and interval of prescribed burning is often determined by operational constraints rather than historical fire regimes, potentially resulting in fire conditions and burn intervals to which native plants are poorly adapted. In this study, we examined how understory vegetation has responded to season and interval of prescribed burning in ponderosa pine (Pinus ponderosa) forests in the Blue Mountains of northeastern Oregon, USA. Using over a decade (2002–2015) of understory vegetation data collected in stands with different intervals (5 versus 15 year) and seasons (spring versus fall) of prescribed burning, we quantified how season and interval of prescribed burning has influenced understory vegetation compositional trajectories and indicator species over time. Season of prescribed burning resulted in different understory communities and distinct trajectories of understory composition over time, but interval of burning did not. Indicator species analysis suggests fall burning is facilitating early seral species, with native annual forbs displaying ephemeral responses to frequent burning, while invasive cheatgrass (Bromus tectorum) increased in abundance and frequency across all treatments over time. These findings indicate that understory vegetation in these ecosystems are sensitive to seasonality of burning, but the responses are subtle. Our findings suggest season and interval of prescribed burning used in this study do not result in large changes in understory vegetation community composition, a key consideration as land managers increase the pace and scale of prescribed fire in these forests. Full article

Cheatgrass (Bromus Tectorum) is a highly invasive species in the Great Basin of the Western USA that is increasing the frequency and intensity of wildland fires. Though cheatgrass plays a significant role in the fire ecology of the Great Basin, very little is known about its combustion emissions. The fresh smoke from 16 open laboratory burns of cheatgrass was analyzed using real-time measurements and filter analysis. We presented measured intensive optical properties of the emitted smoke, including absorption Ångström exponent (AAE), scattering Ångström exponent (SAE), single scattering albedo (SSA), and other combustion properties, such as modified combustion efficiency (MCE) and fuel-based emission factors (EFs). In addition, we gave a detailed chemical analysis of polar organic species in cheatgrass combustion emissions. We presented EFs that showed a large variation between fuels and demonstrated that analysis of combustion emissions for specific fuels was important for studying and modeling the chemistry of biomass-burning emissions. Full article

Invasive annual grasses, such as cheatgrass (Bromus tectorum L.), have proliferated in dryland ecosystems of the western United States, promoting increased fire activity and reduced biodiversity that can be detrimental to socio-environmental systems. Monitoring exotic annual grass cover and dynamics over large areas requires the use of remote sensing that can support early detection and rapid response initiatives. However, few studies have leveraged remote sensing technologies and computing frameworks capable of providing rangeland managers with maps of exotic annual grass cover at relatively high spatiotemporal resolutions and near real-time latencies. Here, we developed a system for automated mapping of invasive annual grass (%) cover using in situ observations, harmonized Landsat and Sentinel-2 (HLS) data, maps of biophysical variables, and machine learning techniques. A robust and automated cloud, cloud shadow, water, and snow/ice masking procedure (mean overall accuracy >81%) was implemented using time-series outlier detection and data mining techniques prior to spatiotemporal interpolation of HLS data via regression tree models (r = 0.94; mean absolute error (MAE) = 0.02). Weekly, cloud-free normalized difference vegetation index (NDVI) image composites (2016–2018) were used to construct a suite of spectral and phenological metrics (e.g., start and end of season dates), consistent with information derived from Moderate Resolution Image Spectroradiometer (MODIS) data. These metrics were incorporated into a data mining framework that accurately (r = 0.83; MAE = 11) modeled and mapped exotic annual grass (%) cover throughout dryland ecosystems in the western United States at a native, 30-m spatial resolution. Our results show that inclusion of weekly HLS time-series data and derived indicators improves our ability to map exotic annual grass cover, as compared to distribution models that use MODIS products or monthly, seasonal, or annual HLS composites as primary inputs. This research fills a critical gap in our ability to effectively assess, manage, and monitor drylands by providing a framework that allows for an accurate and timely depiction of land surface phenology and exotic annual grass cover at spatial and temporal resolutions that are meaningful to local resource managers. Full article

Cheatgrass (Bromus tectorum L.) is one of the most problematic weeds in western United States rangelands and sagebrush steppe. It responds positively to different forms of disturbance, and its management has proven difficult. Herbicide or targeted grazing alone often fail to provide adequate long-term control. Integrating both may afford better control by providing multiple stressors to the weed. We assessed herbicide application, targeted sheep grazing and integrated herbicide and grazing on B. tectorum and the plant community in rangeland in southwestern Montana from 2015 until 2017. Herbicide treatments included spring-applied (May 2015 and 2016) glyphosate, fall-applied (October 2015) glyphosate, imazapic and rimsulfuron, and spring-applied glyphosate plus fall-applied imazapic. Targeted grazing, consisting of four sheep/0.01 ha for a day in 5 m × 20 m plots (all vegetation removed to the ground surface), occurred twice (May 2015 and 2016). While no treatments reduced B. tectorum biomass or seed production, grazing integrated with fall-applied imazapic or rimsulfuron reduced B. tectorum cover from approximately 26% to 14% in 2016 and from 33% to 16% in 2017, compared to ungrazed control plots, and by an even greater amount compared to these herbicides applied without grazing. By 2017, all treatments except spring-applied glyphosate increased total plant cover (excluding B. tectorum) by 8%–12% compared to the control plots, and forbs were generally responsible for this increase. Bromus tectorum management is difficult and our results point to a potential management paradox: Integrating grazing and fall-applied herbicide decreased B. tectorum cover but did not increase native grass cover, while some herbicides without grazing increased native grass cover, but failed to control B. tectorum. Additional research is necessary to determine grazing strategies that will complement herbicide control of B. tectorum while also stimulating native grass recovery, but this initial study demonstrates the potential of integrated management of B. tectorum compared to grazing or herbicide alone. Full article

A fungal pathogen soon to be described as Rutstroemia capillus-albis (Rutstroemiaceae, Helotiales, Leotiomycetes) has been identified as the causal agent of ‘bleach blonde syndrome’ on the invasive annual grass weed Bromus tectorum (cheatgrass) in western North America. This apparently common but previously undescribed disease causes premature senescence and sterility, but does not affect seed germination or seedling emergence and growth. This study investigated whether the new species produces phytotoxins that could be implicated in pathogenesis. The compounds 9-O-methylfusarubin, 9-O-methylbostrycoidin, 5-O-methylnectriafurone, trans-methyl-p-coumarate and terpestacin were isolated from the solid culture of this fungus. The undescribed absolute stereochemistry at C-3 of 9-O-methylfusarubin and at C-1’ of 5-O-methylnectriafurone were assigned by applying electronic and vibrational circular dichroism (ECD and VCD) combined with computational methods and the advanced Mosher’s method, respectively. The first three listed compounds are naphtoquinone pigments, while terpestacin is a sesterterpene, and trans-methyl-p-coumarate could be the product of an unusual fungal phenylpropanoid biosynthesis pathway. In a juvenile plant immersion bioassay, both 9-O-methylfusarubin and terpestacin proved to be highly toxic at 10⁻⁴ M, causing wilting and plant death within 10 days. This finding suggests that these two compounds could play a role in pathogenesis on B. tectorum. Full article